research gap in electric vehicles

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

A review on electric vehicles: technologies and challenges.

1. Introduction

• Zero emissions: this type of vehicles neither emit tailpipe pollutants, CO 2 , nor nitrogen dioxide (NO 2 ). Also, the manufacture processes tend to be more respectful with the environment, although battery manufacturing adversely affects carbon footprint.
• Simplicity: the number of Electric Vehicle (EV) engine elements is smaller, which leads to a much cheaper maintenance. The engines are simpler and more compact, they do not need a cooling circuit, and neither is necessary for incorporating gearshift, clutch, or elements that reduce the engine noise.
• Reliability: having less, and more simple, components makes this type of vehicles have fewer breakdowns. In addition, EVs do not suffer of the inherent wear and tear produced by engine explosions, vibrations, or fuel corrosion.
• Cost: the maintenance cost of the vehicle and the cost of the electricity required is much lower in comparison to maintenance and fuel costs of traditional combustion vehicles. The energy cost per kilometer is significantly lower in EVs than in traditional vehicles, as shown in Figure 1 .
• Comfort: traveling in EVs is more comfortable, due to the absence of vibrations or engine noise [ 2 ].
• Efficiency: EVs are more efficient than traditional vehicles. However, the overall well to wheel (WTW) efficiency will also depend on the power plant efficiency. For instance, total WTW efficiency of gasoline vehicles ranges from 11% to 27%, whereas diesel vehicles range from 25% to 37% [ 3 ]. By contrast, EVs fed by a natural gas power plant show a WTW efficiency that ranges from 13% to 31%, whereas EVs fed by renewable energy show an overall efficiency up to 70%.
• Accessibility: this type of vehicle allows for access to urban areas that are not allowed to other combustion vehicles (e.g., low emissions zones). EVs do not suffer from the same traffic restrictions in large cities, especially at high peaks of contamination level. Interestingly, there was a recent OECD study that suggests that, at least in terms of Particulate Matter (PM) emissions, EVs will unfortunately not improve the air quality situation [ 4 ].
• Driving range: range is typically limited from 200 to 350 km with a full charge, although this issue is being continually improved. For example, the Nissan Leaf has a maximum driving range of 364 km [ 6 ], and the Tesla Model S can reach more than 500 km [ 7 ].
• Charging time: full charging the battery pack can take 4 to 8 h. Even a “fast charge” to 80% capacity can take 30 min. For example, Tesla superchargers can charge the Model S up to 50% in only 20 min, or 80% in half an hour [ 7 ].
• Battery cost: large battery packs are expensive.
• Bulk and weight: battery packs are heavy and take up considerable vehicle space. It is assumed that the batteries of this type of vehicles have an approximate weight of 200 kg [ 8 ], which can vary, depending on the battery capacity.

2. Existing EV-Related Surveys

3. electric vehicles, 3.1. electric vehicles taxonomy.

• Battery Electric Vehicles (BEVs): vehicles 100% are propelled by electric power. BEVs do not have an internal combustion engine and they do not use any kind of liquid fuel. BEVs normally use large packs of batteries in order to give the vehicle an acceptable autonomy. A typical BEV will reach from 160 to 250 km, although some of them can travel as far as 500 km with just one charge. An example of this type of vehicle is the Nissan Leaf [ 24 ], which is 100% electric and it currently provides a 62 kWh battery that allows users to have an autonomy of 360 km.
• Plug-In Hybrid Electric Vehicles (PHEVs): hybrid vehicles are propelled by a conventional combustible engine and an electric engine charged by a pluggable external electric source. PHEVs can store enough electricity from the grid to significantly reduce their fuel consumption in regular driving conditions. The Mitsubishi Outlander PHEV [ 25 ] provides a 12 kWh battery, which allows it to drive around 50 km just with the electric engine. However, it is also noteworthy that PHEVs fuel consumption is higher than indicated by car manufacturers [ 26 ].
• Hybrid Electric Vehicles (HEVs): hybrid vehicles are propelled by a combination of a conventional internal combustion engine and an electric engine. The difference with regard to PHEVs is that HEVs cannot be plugged to the grid. In fact, the battery that provides energy to the electric engine is charged thanks to the power generated by the vehicle’s combustion engine. In modern models, the batteries can also be charged thanks to the energy generated during braking, turning the kinetic energy into electric energy. The Toyota Prius, in its hybrid model (4th generation), provided a 1.3 kWh battery that theoretically allowed it an autonomy as far as 25 km in its all-electric mode [ 27 ].
• Fuel Cell Electric Vehicles (FCEVs): these vehicles are provided with an electric engine that uses a mix of compressed hydrogen and oxygen obtained from the air, having water as the only waste resulting from this process. Although these kinds of vehicles are considered to present “zero emissions”, it is worth highlighting that, although there is green hydrogen, most of the used hydrogen is extracted from natural gas. The Hyundai Nexo FCEV [ 28 ] is an example of this type of vehicles, being able to travel 650 km without refueling.
• Extended-range EVs (ER-EVs): these vehicles are very similar to those ones in the BEV category. However, the ER-EVs are also provided with a supplementary combustion engine, which charges the batteries of the vehicle if needed. This type of engine, unlike those provided by PHEVs and HEVs, is only used for charging, so that it is not connected to the wheels of the vehicle. An example of this type of vehicles is the BMW i3 [ 29 ], which has a 42.2 kWh battery that results in a 260 km autonomy in electric mode, and users can benefit an additional 130 km from the extended-range mode.

3.2. Subsidies and Market Position

4. batteries, 4.1. characteristics of the batteries.

• Capacity. The storage difficulty and cost is one of the main problems of electric power. Currently, this results in the allocation of great amounts of money in the development of new batteries with higher efficiency and reliability, thus improving batteries’ storage capacity. The battery capacity represents the maximum amount of energy that can be extracted from the battery under certain specified conditions. This unit can be expressed in ampere hour (Ah) or in watt hour (Wh), although the latter one is more commonly used by electric vehicles. When considering that, in EVs, the capacity of their batteries is a critical aspect, since it has a direct impact in the vehicles’ autonomy, the emergence of new technologies that enables the storage of a greater energy quantity in the shortest possible time will be a decisive factor in the success of this kind of vehicles. Table 2 shows data that are related to the battery capacities of EVs. As shown, the capacity of batteries is continuously growing and vehicles with more that 100 kWh batteries are expected very soon.
• Charge state. Refers to the battery level with regard to its 100% capacity.
• Energy Density. Obtaining the highest energy density possible is another important aspect in the development of batteries, in other words, that with equal size and weight a battery is able to accumulate a higher energy quantity. The energy density of batteries is measured as the energy that a battery is able to supply per unit volume (Wh/L).
• Specific energy. The energy that a battery is able to provide per unit mass (Wh/kg). Some authors also refer to this feature as energy density, and it can be specified in Wh/L or Wh/kg.
• Specific power. The power that a battery can supply per unit of weight (W/kg).
• Charge cycles. A load cycle is completed when the battery has been used or loaded 100%.
• Lifespan. Another aspect to consider is the batteries lifespan, which is measured in the number of charging cycles that a battery can hold. The goal is to obtain batteries that can endure a greater number of loading and unloading cycles.
• Internal resistance. The components of the batteries are not 100% perfect conductors, which means that they offer a certain resistance to the transmission of electricity. During the charging process, some energy is dispelled in the form of heat (namely, thermal loss). The generated heat per unit of time is equal to the lost power in the resistance, so the internal resistance will have a greater impact in high power charges [ 51 ]. Thus, more energy will be lost during quick charging processes when compared to slow ones. Therefore, it is highly important that batteries can support quick charging and higher temperatures induced due to the internal resistance. In addition, the decrease of this resistance can reduce the charging time that is required, which is one of the most important drawbacks of this type of vehicles today.
• Efficacy. It is the percentage of power that is offered by the battery in relation to the energy charged.

4.2. The Cornerstones: Cost, Capacity, and Charging Time

4.3. different components and battery types.

• Lead-acid batteries (Pb-PbO 2 ). These batteries were invented in 1859 and are the oldest kind of rechargeable battery. Although this kind of battery is very common in conventional vehicles, it has also been used in electric vehicles. It has very low specific energy and energy density ratios. The battery is formed by a sulfuric acid deposit and a group of lead plates. During the initial loading process, the lead sulfate is reduced to metal in the negative plates, while, in the positives, lead oxide is formed (PbO 2 ). The GM EV1 and the Toyota RAV4 EV, are examples of vehicles that used this kind of batteries.
• Nickel-cadmium batteries (Ni-Cd). This technology was used in the 90s, as these batteries have a greater energy density [ 66 ], but they present high memory effect, low lifespan, and cadmium is a very expensive and polluting element. For these reasons, nickel-cadmium batteries are currently being substituted by nickel-metal-hydride (NiMH) batteries.
• Nickel-metal-hydride batteries (Ni-MH). In this type of batteries, an alloy that stores hydrogen is used for negative electrodes instead of cadmium (Cd) [ 67 ]. Although they present a higher level of self discharge than those of nickel-cadmium, these batteries are used by many hybrid vehicles, such as the Toyota Prius and the second version of the GM EV1. The Toyota RAV4 EV, apart from having a lead-acid version, also had another with nickel-metal-hydride.
• Zinc-bromine batteries (Zn-Br 2 ). These kinds of batteries use a zinc-bromine solution stored in two tanks, and in which bromide turns into bromine in the positive electrode. This technology was used by a prototype, called ”T-Star”, in 1993 [ 68 ].
• Sodium chloride and nickel batteries (NA-NiCl). Also being referred to as Zebra, they are very similar to sodium sulfur batteries. Their advantage is that they can offer up to 30% more energy in low temperatures, although its optimum operating range is between 260 °C and 300 °C. These kinds of batteries are ideal for its use in electric vehicles [ 69 ]. The disappeared Modec company used them in 2006.
• Sodium sulfur batteries (Na-S), which contain sodium liquid (Na) and sulfur (S). This type of battery has a high energy density, high loading and unloading efficiency (89–92%), and a long life cycle. In addition, their advantage is that these materials have a very low cost. However, they can reach functioning temperatures of between 300 and 350 °C [ 70 ]. This type of batteries is used in the Ford Ecostar, the model that was launched in 1992–1993.
• Lithium-ion batteries (Li-Ion). These batteries employ, as electrolyte, a lithium salt that provides the necessary ions for the reversible electrochemical reaction that takes place between the cathode and anode. Lithium-ion batteries have the advantages of the lightness of their components, their high loading capacity, their internal resistance, as well as their high loading and unloading cycles. In addition, they present a reduced memory effect.

5. Charging of Electric Vehicles

• AC Level 1. Standard electrical outlet that provides voltage in AC of 120 V offering a maximum intensity of 16 A, which serves a maximum power of 1.9 kW.
• AC Level 2. Standard electrical outlet with 240 V AC and a maximum intensity of 80 A, so it offers a maximum power of 19.2 kW.
• DC Level 1. External charger that by inserting a maximum voltage of 500 V DC with a maximum intensity of 80 A, it provides a maximum power of 40 kW.
• DC Level 2. External charger that, by inserting a maximum voltage of 500 V DC with a maximum intensity of 200 A, provides a maximum power of 100 kW.

5.1. Charging Modes

• Mode 1 (Slow charging). It is defined as a domestic charging mode, with a maximum intensity of 16 A, and it uses a standard single-phase or three-phase power outlet with phase(s), neutral, and protective earth conductors. This mode is the most used in our homes.
• Mode 2 (Semi-fast charging). This mode can be used at home or in public areas, its defined maximum intensity is of 32 A, and, similar to the previous mode, it uses standardized power outlets with phase(s), neutral, and protective earth conductors.
• Mode 3 (Fast charging). It provides an intensity between 32 and 250 A. This charging mode requires the use of an EV Supply Equipment (EVSE), a specific power supply for charging electric vehicles. This device (i.e., the EVSE) provides communication with the vehicles, monitors the charging process, incorporates protection systems, and stops the energy flow when the connection to the vehicle is not detected.
• Mode 4 (Ultra-fast charging). Published in the IEC-62196-3, it defines a direct connection of the EV to the DC supply network with a power intensity of up to 400 A and a maximum voltage of 1000 V, which provides a maximum charging power up to 400 kW. These modes also require an external charger that provides communication between the vehicle and the charging point, as well as protection and control.

5.2. Connectors

• They are sealed solutions (not affected by water or humidity).
• They carry a mechanic or electronic blockage.
• They enable communication with the vehicle.
• Electricity is not supplied until the blockage system is not activated.
• While the blockage system is activated, the vehicle cannot be set in motion, so that a vehicle cannot leave while plugged.
• Some connectors are able to charge in three-phase mode.
• AC pins, two pins to provide power to the vehicle (phase and neutral).
• Ground connection, a security measure, which connects the electrical system to the ground.
• Proximity detection, which avoids the vehicle to move while plugged.
• Pilot Control, which allows communication with the vehicle.
• Type 1 (SAE-J1772-2009) Yazaki. With the aim of finding a standardized connector, the Type 1 AC charging, apart from being included in the SAE-J1772 standard, was also included in the IEC-62196-2. In fact, this connector is commonly found in charging equipments for EVs in North America and Japan [ 80 ], and it is used by a great amount of vehicles, such as the Nissan Leaf, the Chevrolet Volt, the Toyota Prius Prime, the Mitsubishi i-MiEV, the Ford Focus Electric, the Tesla Roadster, and the Tesla Model S. This connector can be observed in Figure 7 a.
• Type 2 (VDE-AR-E 2623-2-2) Mennekes. It was originally designed to be used in the industrial sector, so it was not specifically designed for EVs (see Figure 7 c). In single-phase it is limited up to 230 V, but, in three-phase, is able to hold high voltages and intensities. This connector has 7 pins, i.e., four for the power (in three-phase mode), one ground connection, and two pins to communicate with the vehicle (blockage and communications). An example of a vehicle that uses this connector is the Renault Zoe, which can be charged with the Mennekes connector up to 43 kWh. Although, at first, it was not designed for fast charging, Type 2 also includes another connector, called Combined Charging System (CCS) (see Figure 7 d), being essentially an adapted Mennekes adapted to supply up to 400 A to 1000 V, which would imply a charging power up to 400 kWh [ 81 , 82 ].
• Type 3 (EV Plug Alliance connector) Scame. Single-phase and three-phase connector, designed by the EV Plug Alliance in 2010. It supplies 230 V/400 V and from 16 to 63 A [ 83 ]. France and Italy suggested the use of this connector for their vehicles (see Figure 7 e), but, due to the poor acceptance, the production of Type 3 connectors has been finally abandoned.
• Type 4 (EVS G105-1993) CHAdeMO. Promoted by TEPCO (Tokyo Electric Power Company), it is commonly found in the EVs charging equipment in Japan, although it is also used in Europe and USA (see Figure 7 f). CHAdeMO is designed to supply fast charges in DC. In its first versions, it held up to 400 V, starting the charge with up to 200 A. Nowadays, CHAdeMO chargers have already been designed with 150 kW power, and they aim to reach 350 kW [ 84 ]. This connector has ten pins, two for DC power supply, one for ground connection, and seven pins for communicating with the network. On the 8th of February of 2018, there existed 7133 CHAdeMO charging points in Japan, 6022 in Europe, and 2290 in the USA [ 85 ]. In fact, it is added to numerous vehicles, such as in the Nissan Leaf, the Nissan e-NV200, the Mitsubishi i-MiEV, and the KIA Soul EV.

6. Power Control and Energy Management

Thermal management and power electronics, 7. challenges of the research and open opportunities, 7.1. new challenges and technologies in batteries for evs.

• Lithium iron phosphate (LiFePO 4 ). This kind of battery presents an energy density of approximately 220 Wh/L, a great durability (they are able to withstand between 2000 and 10,000 cycles) and tolerate high temperatures. However, although this type of battery is starting to be tested in EVs [ 94 ], it still can be found in an early stage of research and development. MIT researchers have managed to reduce its weight and they have developed a prototype-cell that can be completely charged in just 10–20 s, a reduced time if we compare it with the necessary 6 min. for standard battery cells [ 95 ].
• Magnesium-ion (Mg-Ion). These batteries change the use of lithium over magnesium, succeeding in storing more than double the charge and increasing its stability. It is expected that this type of battery can have a 6.2 kWh/L energy density [ 96 ], which would imply 8.5 times more than the best lithium batteries, which are currently able to apply up to 0.735 kWh/L. Organizations, such as the Advanced Research Projects Agency-Energy (ARPA-E), Toyota, or NASA, are investigating this type of battery [ 97 , 98 ].
• Lithium-metal. In these batteries, graphite-anode is replaced by a fine lithium-metal layer. This kind of battery is able to store double of the power than a traditional lithium battery [ 99 ]. SolidEnergy Systems, a MIT startup, have already started to deploy this type of batteries in drones, and it is expected that they can be included in EVs [ 100 ]. Lithium-metal batteries have a high Coulombic efficiency (above 99.1%), withstanding more than 6000 charging cycles, and, after 1000 cycles they maintain an average Coulombic efficiency of 98.4% [ 101 ].
• Lithium-air (Li-air). This kind of battery needs a constant supply of oxygen to conduct the reaction with the lithium. They were initially proposed in the 70s, although it was not until recently that have started to be developed and improved. It is expected that its specific energy reaches around 12 kWh/kg (almost 45 times the current of lithium), which would imply being at the same level as the fuel [ 102 ].
• Aluminum-air. Batteries that are developed with this technology produce electricity from the reaction of oxygen with aluminum. Their main advantage is that this type of battery reaches very large energy densities, attaining 6.2 kWh/L [ 103 ], which allows obtaining a high autonomies (up to 1600 km) [ 104 ]. The price of this kind of battery is decreasing, currently positioning in 300 €/kWh [ 105 ], and their advantage is that they are recyclable.
• Sodium-air (Na 2 O 2 ). The company BASF created a Sodium-air battery with an energy density of 4.5 kWh/L [ 106 ]. In electric vehicles, this type of battery can multiply the autonomy of the current lithium batteries at least thirteen times [ 107 ]. A great advantage of this type of batteries is that sodium is the sixth more abundant element in our planet [ 108 ].
• Graphene. Graphene is a material that is formed by pure carbon, which has a high thermal conductivity and it is extremely light (a one square meter blade weighs 0.77 mg) [ 109 ]. One of the major assets of graphene-based batteries is that they barely heat, enabling fast or ultra-fast charges without significant power losses due to heat. Graphenano, a Spanish company, has created a graphene battery that, added to a GTA Spano vehicle (900 hp), has been able to travel 800 km [ 110 ]. In a high power plug, this battery could be charged in only 5 min. This kind of battery is in an early phase of development, although there exist prototypes of graphene batteries with a specific power of 1 kWh/kg, and it is expected to reach 6.4 kWh/kg soon [ 111 ].

7.2. Improvements in the Charging Process

7.3. communications and ai in electric vehicles, 7.4. eco charge and sustainability, 8. conclusions, author contributions, conflicts of interest, abbreviations.

• European Commission. Transport in Figures’—Statistical Pocketbook. 2011. Available online: https://ec.europa.eu/transport/facts-fundings/statistics/pocketbook-2011_en/ (accessed on 21 February 2021).
• Chan, C.C. The state of the art of electric, hybrid, and fuel cell vehicles. Proc. IEEE 2007 , 95 , 704–718. [ Google Scholar ] [ CrossRef ]
• Albatayneh, A.; Assaf, M.N.; Alterman, D.; Jaradat, M. Comparison of the Overall Energy Efficiency for Internal Combustion Engine Vehicles and Electric Vehicles. Environ. Clim. Technol. 2020 , 24 , 669–680. [ Google Scholar ]
• OECD iLibrary. Non-Exhaust Particulate Emissions from Road Transport: An Ignored Environmental Policy Challenge ; Technical Report; OECD Publishing: Paris, France, 2020; Available online: https://doi.org/10.1787/4a4dc6ca-en (accessed on 22 February 2021).
• Blázquez Lidoy, J.; Martín Moreno, J.M. Eficiencia energética en la automoción, el vehículo eléctrico, un reto del presente. Econ. Ind. 2010 , 377 , 76–85. [ Google Scholar ]
• Nissan. Nissan Leaf. Available online: https://www.nissan.co.uk/vehicles/new-vehicles/leaf/range-charging.html (accessed on 20 February 2021).
• Tesla. Tesla Official Website. 2019. Available online: https://www.tesla.com/en_EU/supercharger (accessed on 21 February 2021).
• Berjoza, D.; Jurgena, I. Effects of change in the weight of electric vehicles on their performance characteristics. Agron. Res. 2017 , 15 , 952–963. [ Google Scholar ]
• Yong, J.Y.; Ramachandaramurthy, V.K.; Tan, K.M.; Mithulananthan, N. A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects. Renew. Sustain. Energy Rev. 2015 , 49 , 365–385. [ Google Scholar ] [ CrossRef ]
• Richardson, D.B. Electric vehicles and the electric grid: A review of modeling approaches, Impacts, and renewable energy integration. Renew. Sustain. Energy Rev. 2013 , 19 , 247–254. [ Google Scholar ] [ CrossRef ]
• Habib, S.; Kamran, M.; Rashid, U. Impact analysis of vehicle-to-grid technology and charging strategies of electric vehicles on distribution networks—A review. J. Power Sources 2015 , 277 , 205–214. [ Google Scholar ] [ CrossRef ]
• Liu, L.; Kong, F.; Liu, X.; Peng, Y.; Wang, Q. A review on electric vehicles interacting with renewable energy in smart grid. Renew. Sustain. Energy Rev. 2015 , 51 , 648–661. [ Google Scholar ] [ CrossRef ]
• Hawkins, T.R.; Gausen, O.M.; Strømman, A.H. Environmental impacts of hybrid and electric vehicles—A review. Int. J. Life Cycle Assess. 2012 , 17 , 997–1014. [ Google Scholar ] [ CrossRef ]
• Vasant, P.; Marmolejo, J.A.; Litvinchev, I.; Aguilar, R.R. Nature-inspired meta-heuristics approaches for charging plug-in hybrid electric vehicle. Wirel. Netw. 2019 , 26 , 4753–4766. [ Google Scholar ] [ CrossRef ]
• Shuai, W.; Maillé, P.; Pelov, A. Charging electric vehicles in the smart city: A survey of economy-driven approaches. IEEE Trans. Intell. Transp. Syst. 2016 , 17 , 2089–2106. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Tan, K.M.; Ramachandaramurthy, V.K.; Yong, J.Y. Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques. Renew. Sustain. Energy Rev. 2016 , 53 , 720–732. [ Google Scholar ] [ CrossRef ]
• Hu, J.; Morais, H.; Sousa, T.; Lind, M. Electric vehicle fleet management in smart grids: A review of services, optimization and control aspects. Renew. Sustain. Energy Rev. 2016 , 56 , 1207–1226. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Rahman, I.; Vasant, P.M.; Singh, B.S.M.; Abdullah-Al-Wadud, M.; Adnan, N. Review of recent trends in optimization techniques for plug-in hybrid, and electric vehicle charging infrastructures. Renew. Sustain. Energy Rev. 2016 , 58 , 1039–1047. [ Google Scholar ] [ CrossRef ]
• Mahmud, K.; Town, G.E.; Morsalin, S.; Hossain, M. Integration of electric vehicles and management in the internet of energy. Renew. Sustain. Energy Rev. 2018 , 82 , 4179–4203. [ Google Scholar ] [ CrossRef ]
• Das, H.; Rahman, M.; Li, S.; Tan, C. Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review. Renew. Sustain. Energy Rev. 2020 , 120 , 109618. [ Google Scholar ] [ CrossRef ]
• Li, Y.; Liu, K.; Foley, A.M.; Zülke, A.; Berecibar, M.; Nanini-Maury, E.; Van Mierlo, J.; Hoster, H.E. Data-driven health estimation and lifetime prediction of lithium-ion batteries: A review. Renew. Sustain. Energy Rev. 2019 , 113 , 109254. [ Google Scholar ] [ CrossRef ]
• Liu, K.; Li, Y.; Hu, X.; Lucu, M.; Widanage, W.D. Gaussian Process Regression With Automatic Relevance Determination Kernel for Calendar Aging Prediction of Lithium-Ion Batteries. IEEE Trans. Ind. Inform. 2020 , 16 , 3767–3777. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Hu, X.; Zhang, K.; Liu, K.; Lin, X.; Dey, S.; Onori, S. Advanced Fault Diagnosis for Lithium-Ion Battery Systems: A Review of Fault Mechanisms, Fault Features, and Diagnosis Procedures. IEEE Ind. Electron. Mag. 2020 , 14 , 65–91. [ Google Scholar ] [ CrossRef ]
• insideEVs. Nissan Reveals LEAF e-Plus: 62 kWh Battery, 226-Mile Range. 2019. Available online: https://insideevs.com/nissan-reveals-leaf-e-plus-ces/ (accessed on 17 February 2021).
• Mitsubishi Motors. Mitsubishi Outlander PHEV 2018. 2019. Available online: https://www.mitsubishicars.com/outlander-phev/2018/specifications (accessed on 17 February 2021).
• Plötz, P.; Moll, C.; Bieker, G.; Mock, P.; Li, Y. Real-World Usage of Plug-In Hybrid Electric Vehicles: Fuel Consumption, Electric Driving, and CO 2 Emissions ; Technical Report; International Council on Clean Transportation Europe (ICCT): Washington, DC, USA, 2020; Available online: https://theicct.org/sites/default/files/publications/PHEV-white%20paper-sept2020-0.pdf (accessed on 22 February 2021).
• The Car Guide. 2014 Toyota Prius PHV: To Plug in or Not to Plug in? 2014. Available online: https://www.guideautoweb.com/en/articles/21152/2014-toyota-prius-phv-to-plug-in-or-not-to-plug-in/ (accessed on 21 February 2021).
• Hyundai. All-New Hyundai NEXO—Technical Specifications. 2019. Available online: https://www.hyundai.news/eu/press-kits/all-new-hyundai-nexo-technical-specifications/ (accessed on 21 February 2021).
• insideEVs. 2019 BMW i3, i3 REx, i3s & i3s REx: Full Specs. 2019. Available online: https://insideevs.com/2019-bmw-i3-rex-i3s-rex-full-spec/ (accessed on 21 February 2021).
• EVvolumes.com. The Electric Vehicle World Sales Database. 2019. Available online: http://www.ev-volumes.com/ (accessed on 19 February 2021).
• Framework Convention on Climate Change. Adoption of the Paris Agreement ; Technical Report FCCC/CP/2015/L.9/Rev.1; United Nations: New York, NY, USA, 2015; Available online: http://unfccc.int/resource/docs/2015/cop21/eng/l09r01.pdf (accessed on 20 February 2021).
• Forocoches Electricos. Los Incentivos al Coche Eléctrico Están Creciendo en Toda Europa. 2017. Available online: http://forococheselectricos.com/2017/09/incentivos-al-coche-electrico-europa.html (accessed on 19 February 2021).
• Vicepresidencia del Gobierno. Boletín Oficial del Estado. Technical Report, Agencia Estatal. 2017. Available online: http://www.boe.es/boe/dias/2017/11/15/pdfs/BOE-A-2017-13158.pdf (accessed on 20 February 2021).
• Movilidad Eléctrica. La Exención del IVA en Noruega para los Coches Eléctricos se Amplía Hasta 2020. 2016. Available online: https://movilidadelectrica.com/la-exencion-del-iva-en-noruega-se-amplia-2020/ (accessed on 21 February 2021).
• Institute of Transport Economics, Norwegian Centre for Transport Research. Available online: https://www.toi.no/ (accessed on 21 February 2021).
• Electric Car Use by Country. Available online: https://en.wikipedia.org/wiki/Electric_car_use_by_country (accessed on 21 February 2021).
• European Alternative Fuels Observatory. Available online: http://www.eafo.eu/ (accessed on 21 February 2021).
• Electric Car Use by Country. The Electric Vehicles world Sales Database. Available online: http://www.ev-volumes.com/ (accessed on 21 February 2021).
• Statista. Electric Vehicles Worldwide. Available online: https://www.statista.com/study/11578/electric-vehicles-statista-dossier/ (accessed on 21 February 2021).
• Hong Kong Bussiness. EV Dossier. Available online: https://hongkongbusiness.hk/transport-logistics/news/ev-sales-surge-in-2020-analyst (accessed on 21 February 2021).
• EVAdoption.com. Analyzing Key Factors That Will Drive Mass Adoption of Electric Vehicles. 2019. Available online: https://evadoption.com/ev-market-share/ (accessed on 19 February 2021).
• CNN. These Countries Want to Ban Gas and Diesel Cars. 2017. Available online: http://money.cnn.com/2017/09/11/autos/countries-banning-diesel-gas-cars/index.html (accessed on 18 February 2021).
• The Times of Israel. Israel Aims to Eliminate Use of Coal, Gasoline and Diesel by 2030. 2018. Available online: https://www.timesofisrael.com/israel-aims-to-eliminate-use-of-coal-gasoline-and-diesel-by-2030/ (accessed on 20 February 2021).
• NLTimes. New Dutch Government’s Plans for the Coming Years. 2017. Available online: https://nltimes.nl/2017/10/10/new-dutch-governments-plans-coming-years (accessed on 20 February 2021).
• Newsweek. Electric Cars only: California Bill Would Ban Gas-Powered Cars by 2040. 2017. Available online: http://www.newsweek.com/california-ban-gas-powered-cars-2040-740584 (accessed on 20 February 2021).
• The Guardian. German Court Rules Cities Can Ban Diesel Cars to Tackle Pollution. 2018. Available online: https://www.theguardian.com/environment/2018/feb/27/german-court-rules-cities-can-ban-diesel-cars-to-tackle-pollution (accessed on 20 February 2021).
• Drive Mag. Paris to Ban Diesel Cars from 2024, All Internal Combustion Vehicles from 2030. 2017. Available online: https://drivemag.com/news/paris-to-ban-diesel-cars-from-2024-all-internal-combustion-vehicles-from-2030 (accessed on 20 February 2021).
• Electrek. Rome Latest City to Announce Car Ban, Will Ban Diesel Cars from Historical Center Starting 2024. 2018. Available online: https://electrek.co/2018/02/28/rome-bans-diesel-cars-2024/ (accessed on 20 February 2021).
• Cheat Sheet. 10 Best-Selling Electric Vehicles of All Time. Available online: https://www.cheatsheet.com/automobiles/best-selling-electric-vehicles-of-all-time.html/?a=viewall (accessed on 18 February 2021).
• Inside-EVs. EV Battery Makers 2016: Panasonic and BYD Combine to Hold Majority of Market. 2017. Available online: https://insideevs.com/ev-battery-makers-2016-panasonic-and-byd-combine-to-hold-majority-of-market/ (accessed on 21 February 2021).
• Schweiger, H.G.; Obeidi, O.; Komesker, O.; Raschke, A.; Schiemann, M.; Zehner, C.; Gehnen, M.; Keller, M.; Birke, P. Comparison of several methods for determining the internal resistance of lithium ion cells. Sensors 2010 , 10 , 5604–5625. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Green Car Reports. Lithium-Ion Battery Packs Now 209 per kwh, Will Fall to 100 by 2025: Bloomberg Analysis. Available online: https://www.greencarreports.com/news/1114245_lithium-ion-battery-packs-now-209-per-kwh-will-fall-to-100-by-2025-bloomberg-analysis (accessed on 18 February 2021).
• Tesla. Gigafactory. 2014. Available online: https://www.tesla.com/esES/blog/gigafactory (accessed on 21 February 2021).
• Clean Technica. Tesla Batteries 101—Production Capacity, Uses, Chemistry, & Future Plans. 2017. Available online: https://cleantechnica.com/2017/12/02/tesla-batteries-101-production-capacity-uses-chemistry-future-plans/ (accessed on 21 February 2021).
• Sustainable Energy Authority of Ireland. Hybrid Electric and Battery Electric Vehicles ; AEA Energy & Environment: Dublin, Ireland, 2007. [ Google Scholar ]
• Post, T.J. Better Place Unveils Battery-Swap Network. 2012. Available online: http://www.jpost.com/Business/Business-News/Better-Place-unveils-battery-swap-network (accessed on 21 February 2021).
• The Times of Israel. Available online: https://www.timesofisrael.com/where-better-place-failed-israeli-engineers-seek-to-help-china-succeed/ (accessed on 23 February 2021).
• Times, T.N.Y. Better Place Opens Battery-Swap Station in Tokyo for 90-Day Taxi Trial. 2011. Available online: http://wheels.blogs.nytimes.com/2010/04/29/better-place-opens-battery-swap-station-in-tokyo-for-90-day-taxi-trial/?_r=0 (accessed on 21 February 2021).
• CNN. Tesla Unveils 90-Second Battery-Pack Swap. 2011. Available online: http://money.cnn.com/2013/06/21/autos/tesla-battery-swap/ (accessed on 21 February 2021).
• Mahony, H. Denmark to Be Electric Cars Guinea Pig. 2011. Available online: https://euobserver.com/transport/32458 (accessed on 21 February 2021).
• Adler, J.D.; Mirchandani, P.B. Online routing and battery reservations for electric vehicles with swappable batteries. Transp. Res. Part B: Methodol. 2014 , 70 , 285–302. [ Google Scholar ] [ CrossRef ]
• Mak, H.Y.; Rong, Y.; Shen, Z.J.M. Infrastructure planning for electric vehicles with battery swapping. Manag. Sci. 2013 , 59 , 1557–1575. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Yang, S.; Yao, J.; Kang, T.; Zhu, X. Dynamic operation model of the battery swapping station for EV (electric vehicle) in electricity market. Energy 2014 , 65 , 544–549. [ Google Scholar ] [ CrossRef ]
• Storandt, S.; Funke, S. Cruising with a Battery-Powered Vehicle and Not Getting Stranded. In Proceedings of the Twenty-Sixth AAAI Conference on Artificial Intelligence and the Twenty-Fourth Innovative Applications of Artificial Intelligence Conference, Toronto, ON, Canada, 22–26 July 2012; Volume 3, p. 46. [ Google Scholar ]
• Jing, W.; Yan, Y.; Kim, I.; Sarvi, M. Electric vehicles: A review of network modelling and future research needs. Adv. Mech. Eng. 2016 , 8 . [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Haschka, F.; Schlieck, D. High power nickel-cadmium cells with fiber electrodes (FNC). In Proceedings of the 32nd International Power Sources Symposium, Cherry Hill, NJ, USA, 9–12 June 1986. [ Google Scholar ]
• Maggetto, G.; Mierlo, J.V. Electric and electric hybrid vehicle technology: A survey. In Proceedings of the IEE Seminar Electric, Hybrid and Fuel Cell Vehicles (Ref. No. 2000/050), Durham, UK, 11 April 2000. [ Google Scholar ] [ CrossRef ]
• Swan, D.H.; Dickinson, B.; Arikara, M.; Tomazic, G.S. Demonstration of a zinc bromine battery in an electric vehicle. In Proceedings of the 9th Annual Battery Conference on Applications and Advances, Long Beach, CA, USA, 11–13 January 1994; pp. 104–109. [ Google Scholar ] [ CrossRef ]
• Sessa, S.D.; Crugnola, G.; Todeschini, M.; Zin, S.; Benato, R. Sodium nickel chloride battery steady-state regime model for stationary electrical energy storage. J. Energy Storage 2016 , 6 , 105–115. [ Google Scholar ] [ CrossRef ]
• Sudworth, J.; Tiley, A. Sodium Sulphur Battery ; Springer: Berlin/Heidelberg, Germany, 1985. [ Google Scholar ]
• Lu, L.; Han, X.; Li, J.; Hua, J.; Ouyang, M. A review on the key issues for lithium-ion battery management in electric vehicles. J. Power Sources 2013 , 226 , 272–288. [ Google Scholar ] [ CrossRef ]
• Du Pasquier, A.; Plitz, I.; Menocal, S.; Amatucci, G. A comparative study of Li-ion battery, supercapacitor and nonaqueous asymmetric hybrid devices for automotive applications. J. Power Sources 2003 , 115 , 171–178. [ Google Scholar ] [ CrossRef ]
• SAE International. Vehicle Architecture for Data Communications Standards—Class B Data Communications Network Interface ; Standard; SAE International: Warrendale, PA, USA, 2009. [ Google Scholar ]
• International Electrotechnical Commission. Plugs, Socket-Outlets, Vehicle Couplers and Vehicle Inlets—Conductive Charging of Electric Vehicles—Part 1: General Requirements ; Standard; IEC: Geneva, Switzerland, 2014. [ Google Scholar ]
• Sbordone, D.; Bertini, I.; Di Pietra, B.; Falvo, M.C.; Genovese, A.; Martirano, L. EV fast charging stations and energy storage technologies: A real implementation in the smart micro grid paradigm. Electr. Power Syst. Res. 2015 , 120 , 96–108. [ Google Scholar ] [ CrossRef ]
• CQC. Available online: http://www.cqc.com.cn/dynamic/contentcore/resource/download?ID=32242 (accessed on 21 February 2021).
• EVEXPERT. Connector Types for EV Charging around the World. Available online: https://www.evexpert.eu/tips-advices-manual-curiosities-information-electromobility-evexpert/basics-of-electromobility-basic-abc/connector-types-for-ev-charging-around-the-world (accessed on 5 March 2021).
• CAD-block.com. Electric Vehicle Connector Free CAD Drawings. Available online: https://cad-block.com/508-electric-vehicle-connector.html (accessed on 5 March 2021).
• Bakker, S.; Leguijt, P.; van Lente, H. Niche accumulation and standardization—The case of electric vehicle recharging plugs. J. Clean. Prod. 2015 , 94 , 155–164. [ Google Scholar ] [ CrossRef ]
• Phoenix Contact. Solutions for E-Mobility ; Technical Report; Phoenix Contact: Blomberg, Germany, 2015; Available online: http://www.mouser.com/pdfdocs/PhoenixContactsolutionsbrochurefore-mobility.pdf (accessed on 21 February 2021).
• Mennekes. Industrial Plugs and Receptacles ; Technical Report; Mennekes: Kirchhundem, Germany, 2010; Available online: http://www.mennekes.com/pdf/intl/MENNEKES%202010%20Short%20Form%20Export%20Catalog.pdf (accessed on 21 February 2021).
• Electroenchufe. Mennekes.de—Electro Enchufe Sac ; Technical Report; Electroenchufe: Lima, Peru, 2010. [ Google Scholar ]
• Scamme. Libera—Scame Parre s.p.a. Technical Report. 2010. Available online: http://www.scame.com/doc/ZP00833-IB-1.pdf (accessed on 21 February 2021).
• CHAdeMO Association. CHAdeMO Announces High Power (150 KW) Version of the Protocol ; Technical Report; CHAdeMO Association: Paris, France, 2016. [ Google Scholar ]
• CHAdeMO Association. CHAdeMO’s Fast Charging Station in the World. Available online: http://www.chademo.com/ (accessed on 21 February 2021).
• International Energy Agency. Technical Guidelines on Charging Facilities for Electric Vehicles ; Technical Report; Goverment of Hong Kong: Hong Kong, China, 2015. Available online: https://www.emsd.gov.hk/filemanager/en/content444/ChargingFacilitiesElectricVehicles.pdf (accessed on 2 February 2021).
• Hauser, A.; Kuhn, R. High-voltage battery management systems (BMS) for electric vehicles. In Advances in Battery Technologies for Electric Vehicles ; Elsevier: Amsterdam, The Netherlands, 2015; pp. 265–282. [ Google Scholar ]
• Xing, Y.; Ma, E.W.; Tsui, K.L.; Pecht, M. Battery management systems in electric and hybrid vehicles. Energies 2011 , 4 , 1840–1857. [ Google Scholar ] [ CrossRef ]
• Zhang, S.; Luo, Y.; Wang, J.; Wang, X.; Li, K. Predictive Energy Management Strategy for Fully Electric Vehicles Based on Preceding Vehicle Movement. IEEE Trans. Intell. Transp. Syst. 2017 , 18 , 3049–3060. [ Google Scholar ] [ CrossRef ]
• Shang, Y.; Liu, K.; Cui, N.; Zhang, Q.; Zhang, C. A Sine-Wave Heating Circuit for Automotive Battery Self-Heating at Subzero Temperatures. IEEE Trans. Ind. Inform. 2020 , 16 , 3355–3365. [ Google Scholar ] [ CrossRef ]
• Shang, Y.; Liu, K.; Cui, N.; Wang, N.; Li, K.; Zhang, C. A Compact Resonant Switched-Capacitor Heater for Lithium-Ion Battery Self-Heating at Low Temperatures. IEEE Trans. Power Electron. 2020 , 35 , 7134–7144. [ Google Scholar ] [ CrossRef ]
• Nonneman, J.; T’Jollyn, I.; Clarie, N.; Weckx, S.; Sergeant, P.; De Paepe, M. Model-Based Comparison of Thermo-Hydraulic Performance of Various Cooling Methods for Power Electronics of Electric Vehicles. In Proceedings of the 2018 17th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), San Diego, CA, USA, 29 May–1 June 2018; pp. 398–409. [ Google Scholar ]
• Mouawad, B.; Espina, J.; Li, J.; Empringham, L.; Johnson, C.M. Novel Silicon Carbide Integrated Power Module for EV application. In Proceedings of the 2018 1st Workshop on Wide Bandgap Power Devices and Applications in Asia (WiPDA Asia), Xi’an, China, 7–19 May 2018; pp. 176–180. [ Google Scholar ]
• Millner, A. Modeling lithium ion battery degradation in electric vehicles. In Proceedings of the IEEE Conference on Innovative Technologies for an Efficient and Reliable Electricity Supply (CITRES), Waltham, MA, USA, 27–29 September 2010; pp. 349–356. [ Google Scholar ]
• Alternative Energy. New Battery Technology Charges in Seconds. 2009. Available online: http://www.alternative-energy-news.info/new-battery-technology-charges-in-seconds/ (accessed on 21 February 2021).
• Zhao-Karger, Z.; Fichtner, M. Magnesium–sulfur battery: Its beginning and recent progress. MRS Commun. 2017 , 7 , 770–784. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Seeker. Supercharged! Battery Power for the Future. Available online: https://www.seeker.com/supercharged-battery-power-for-the-future-1766230400.html (accessed on 21 February 2021).
• NASA. A Multiscale Approach to Magnesium Intercalation Batteries: Safer, Lighter, and Longer-Lasting. Available online: https://www.nasa.gov/directorates/spacetech/strg/nstrf_2017/Magnesium_Intercalation_Batteries (accessed on 21 February 2021).
• MIT Technology Review. A Battery for Electronics That Lasts Twice as Long. 2015. Available online: https://www.technologyreview.com/s/534626/a-battery-for-electronics-that-lasts-twice-as-long/ (accessed on 21 February 2021).
• MIT Technology Review. Better Lithium Batteries to Get a Test Flight. 2016. Available online: https://www.technologyreview.com/s/602197/better-lithium-batteries-to-get-a-test-flight/ (accessed on 21 February 2021).
• Qian, J.; Henderson, W.A.; Xu, W.; Bhattacharya, P.; Engelhard, M.; Borodin, O.; Zhang, J.G. High rate and stable cycling of lithium metal anode. Nat. Commun. 2015 , 6 , 6362. [ Google Scholar ] [ CrossRef ] [ PubMed ] [ Green Version ]
• Kosivi, J.; Gomez, J.; Nelson, R.; Kalu, E.E.; Weatherspoon, M.H. Non-Paste Based Composite Cathode Electrode for Lithium Air Battery ; ECS Meeting Abstracts; The Electrochemical Society: Pennington, NJ, USA, 2014; p. 206. [ Google Scholar ]
• Gelman, D.; Shvartsev, B.; Ein-Eli, Y. Aluminum–air battery based on an ionic liquid electrolyte. J. Mater. Chem. A 2014 , 2 , 20237–20242. [ Google Scholar ] [ CrossRef ]
• Extremetech. Aluminium-Air Battery Can Power Electric Vehicles for 1000 Miles, Will Come to Production Cars in 2017. Available online: https://www.extremetech.com/extreme/151801-aluminium-air-battery-can-power-electric-vehicles-for-1000-miles-will-come-to-production-cars-in-2017 (accessed on 21 February 2021).
• Energy Storage Inter-Platform Group. State of the Art of Energy Storage Regulations and Technology. Available online: http://www.futured.es/wp-content/uploads/2016/06/GIA-Maqueta_eng.pdf (accessed on 21 February 2021).
• Adelhelm, P.; Hartmann, P.; Bender, C.L.; Busche, M.; Eufinger, C.; Janek, J. From lithium to sodium: Cell chemistry of room temperature sodium–air and sodium–sulfur batteries. Beilstein J. Nanotechnol. 2015 , 6 , 1016. [ Google Scholar ] [ CrossRef ]
• Cleantechnica. Sodium-Air Batteries May Best Lithium-Air Batteries. 2013. Available online: https://cleantechnica.com/2013/03/20/sodium-air-batteries-may-best-lithium-air-batteries/ (accessed on 21 February 2021).
• Phys.org. Sodium-Air Battery Offers Rechargeable Advantages Compared to Li-Air Batteries. 2013. Available online: https://phys.org/news/2013-01-sodium-air-battery-rechargeable-advantages-li-air.html (accessed on 21 February 2021).
• Vargas-Ceballos, O.A. Estudio de Materiales Basados en Grafeno para su uso Como Ánodos en Baterías de Li-Ión. Ph.D. Thesis, Universidad de Córdoba, Cordoba, Spain, 2013. [ Google Scholar ]
• García, F. La Española Graphenano Presenta una Batería que Dura 800 Kilómetros. 2016. Available online: http://www.elmundo.es/motor/2016/02/11/56bc7d6aca4741e31e8b461f.html (accessed on 21 February 2021).
• Kim, H.; Park, K.Y.; Hong, J.; Kang, K. All-graphene-battery: Bridging the gap between supercapacitors and lithium ion batteries. Sci. Rep. 2014 , 4 , 5278. [ Google Scholar ] [ CrossRef ]
• Zhang, G.; Tan, T.; Wang, G. Real-Time Smart Charging of Electric Vehicles for Demand Charge Reduction at Non-Residential Sites. IEEE Trans. Smart Grid 2017 . [ Google Scholar ] [ CrossRef ]
• García-Álvarez, J.; González, M.A.; Vela, C.R. Metaheuristics for solving a real-world electric vehicle charging scheduling problem. Appl. Soft Comput. 2018 , 65 , 292–306. [ Google Scholar ] [ CrossRef ]
• Torres-Sanz, V.; Sanguesa, J.; Martinez, F.; Garrido, P.; Marquez-Barja, J. Enhancing the charging process of electric vehicles at residential homes. IEEE Access 2018 , 6 , 22875–22888. [ Google Scholar ] [ CrossRef ]
• Thomas, J.J.; Karagoz, P.; Ahamed, B.B.; Vasant, P. Deep Learning Techniques and Optimization Strategies in Big Data Analytics ; IGI Global: Hershey, PA, USA, 2020; pp. 1–355. [ Google Scholar ] [ CrossRef ]
• Lukic, S.; Pantic, Z. Cutting the Cord: Static and Dynamic Inductive Wireless Charging of Electric Vehicles. IEEE Electrif. Mag. 2013 , 1 , 57–64. [ Google Scholar ] [ CrossRef ]
• Manshadi, S.D.; Khodayar, M.E.; Abdelghany, K.; Üster, H. Wireless Charging of Electric Vehicles in Electricity and Transportation Networks. IEEE Trans. Smart Grid 2018 , 9 , 4503–4512. [ Google Scholar ] [ CrossRef ]
• Dai, J.; Ludois, D.C. A Survey of Wireless Power Transfer and a Critical Comparison of Inductive and Capacitive Coupling for Small Gap Applications. IEEE Trans. Power Electron. 2015 , 30 , 6017–6029. [ Google Scholar ] [ CrossRef ]
• Li, L.; Wang, Z.; Gao, F.; Wang, S.; Deng, J. A family of compensation topologies for capacitive power transfer converters for wireless electric vehicle charger. Appl. Energy 2020 , 260 , 114156. [ Google Scholar ] [ CrossRef ]
• Nohara, J.; Omori, H.; Yamamoto, A.; Kimura, N.; Morizane, T. A Miniaturized Single-Ended Wireless EV Charger with New High Power-Factor Drive and Natural Cooling Structure. In Proceedings of the 2018 IEEE International Power Electronics and Application Conference and Exposition (PEAC), Shenzhen, China, 4–7 November 2018; pp. 1–6. [ Google Scholar ]
• Wang, Y.; Yuan, R.; Jiang, Z.; Zhao, S.; Zhao, W.; Huang, X. Research on Dynamic Wireless EV Charging Power Control Method Based on Parameter Adjustment according to Driving Speed. In Proceedings of the 2019 IEEE 2nd International Conference on Electronics Technology (ICET), Chengdu, China, 10–13 May 2019; pp. 305–309. [ Google Scholar ]
• Masikos, M.; Demestichas, K.; Adamopoulou, E.; Theologou, M. Machine-learning methodology for energy efficient routing. IET Intell. Transp. Syst. 2013 , 8 , 255–265. [ Google Scholar ] [ CrossRef ]
• Alesiani, F.; Maslekar, N. Optimization of Charging Stops for Fleet of Electric Vehicles: A Genetic Approach. IEEE Intell. Transp. Syst. Mag. 2014 , 6 , 10–21. [ Google Scholar ] [ CrossRef ]
• Sugii, Y.; Tsujino, K.; Nagano, T. A genetic-algorithm based scheduling method of charging electric vehicles. In Proceedings of the 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No. 99CH37028), Tokyo, Japan, 12–15 October 1999; Volume 4, pp. 435–440. [ Google Scholar ] [ CrossRef ]
• Panahi, D.; Deilami, S.; Masoum, M.A.S.; Islam, S.M. Forecasting plug-in electric vehicles load profile using artificial neural networks. In Proceedings of the 2015 Australasian Universities Power Engineering Conference (AUPEC), Wollongong, Australia, 27–30 September 2015; pp. 1–6. [ Google Scholar ] [ CrossRef ]
• Park, J.; Kim, Y. Supervised-Learning-Based Optimal Thermal Management in an Electric Vehicle. IEEE Access 2020 , 8 , 1290–1302. [ Google Scholar ] [ CrossRef ]
• Karimi, G.; Li, X. Thermal management of lithium-ion batteries for electric vehicles. Int. J. Energy Res. 2013 , 37 , 13–24. [ Google Scholar ] [ CrossRef ]
• Held, M.; Baumann, M. Assessment of the Environmental Impacts of Electric Vehicle Concepts. In Towards Life Cycle Sustainability Management ; Finkbeiner, M., Ed.; Springer: Dordrecht, The Netherlands, 2011; pp. 535–546. [ Google Scholar ]
• Romare, M.; Dahllöf, L. The Life Cycle Energy Consumption and Greenhouse Gas Emissions from Lithium-Ion Batteries: A Study with Focus on Current Technology and Batteries for Light-Duty Vehicles ; Technical Report; IVL Swedish Environmental Research Institute: Stockholm, Sweden, 2017; Available online: https://www.ivl.se/download/18.5922281715bdaebede9559/1496046218976/C243+The+life+cycle+energy+consumption+and+CO2+emissions+from+lithium+ion+batteries+.pdf (accessed on 12 February 2021).
• Hsu, T.R. On the Sustainability of Electrical Vehicles. In Proceedings of the IEEE Green Energy and Systems Conference (IGESC), Long Beach, CA, USA, 25 November 2013; pp. 1–7. [ Google Scholar ]
• Buchal, C.; Karl, H.D.; Mult, H.C. Hans-Werner Sinn. Kohlemotoren, Windmotoren und Dieselmotoren: Was zeigt die CO 2 -Bilanz? Ifo Schnelld. 2019 , 72 , 40–54. [ Google Scholar ]
• Burger, B. Net Public Electricity Generation in Germany in 2018 ; Technical Report; Fraunhofer Institute for Solar Energy Systems (ISE): Freiburg, Germany, 2019; Available online: https://www.ise.fraunhofer.de/content/dam/ise/en/documents/publications/studies/Stromerzeugung_2017_e.pdf (accessed on 12 February 2021).
• Saber, A.Y.; Venayagamoorthy, G.K. Plug-in vehicles and renewable energy sources for cost and emission reductions. IEEE Trans. Ind. Electron. 2011 , 58 , 1229–1238. [ Google Scholar ] [ CrossRef ]
• Verzijlbergh, R.A.; De Vries, L.J.; Lukszo, Z. Renewable energy sources and responsive demand. Do we need congestion management in the distribution grid? IEEE Trans. Power Syst. 2014 , 29 , 2119–2128. [ Google Scholar ] [ CrossRef ]
• Hu, W.; Su, C.; Chen, Z.; Bak-Jensen, B. Optimal operation of plug-in electric vehicles in power systems with high wind power penetrations. IEEE Trans. Sustain. Energy 2013 , 4 , 577–585. [ Google Scholar ]
• Vasirani, M.; Kota, R.; Cavalcante, R.L.G.; Ossowski, S.; Jennings, N.R. An Agent-Based Approach to Virtual Power Plants of Wind Power Generators and Electric Vehicles. IEEE Trans. Smart Grid 2013 , 4 , 1314–1322. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Schuller, A.; Hoeffer, J. Assessing the impact of EV mobility patterns on renewable energy oriented charging strategies. Energy Procedia 2014 , 46 , 32–39. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Bhatti, A.R.; Salam, Z.; Aziz, M.J.B.A.; Yee, K.P.; Ashique, R.H. Electric vehicles charging using photovoltaic: Status and technological review. Renew. Sustain. Energy Rev. 2016 , 54 , 34–47. [ Google Scholar ] [ CrossRef ]
• Calise, F.; Cappiello, F.L.; Cartenì, A.; d’Accadia, M.D.; Vicidomini, M. A novel paradigm for a sustainable mobility based on electric vehicles, photovoltaic panels and electric energy storage systems: Case studies for Naples and Salerno (Italy). Renew. Sustain. Energy Rev. 2019 , 111 , 97–114. [ Google Scholar ] [ CrossRef ]
• Jungst, R.G. Recycling of electric vehicle batteries. In Used Battery Collection and Recycling ; Pistoia, G., Wiaux, J.P., Wolsky, S., Eds.; Elsevier: Amsterdam, The Netherlands, 2001; Volume 10, pp. 295–327. [ Google Scholar ] [ CrossRef ]
• Aasness, M.A.; Odeck, J. The increase of electric vehicle usage in Norway—Incentives and adverse effects. Eur. Transp. Res. Rev. 2015 , 7 , 34. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• National Statistical Institute of Norway. Public Transport Statistics. 2019. Available online: https://www.ssb.no/en/transport-og-reiseliv/statistikker/kolltrans (accessed on 12 February 2021).

Click here to enlarge figure

Share and Cite

Sanguesa, J.A.; Torres-Sanz, V.; Garrido, P.; Martinez, F.J.; Marquez-Barja, J.M. A Review on Electric Vehicles: Technologies and Challenges. Smart Cities 2021 , 4 , 372-404. https://doi.org/10.3390/smartcities4010022

Sanguesa JA, Torres-Sanz V, Garrido P, Martinez FJ, Marquez-Barja JM. A Review on Electric Vehicles: Technologies and Challenges. Smart Cities . 2021; 4(1):372-404. https://doi.org/10.3390/smartcities4010022

Sanguesa, Julio A., Vicente Torres-Sanz, Piedad Garrido, Francisco J. Martinez, and Johann M. Marquez-Barja. 2021. "A Review on Electric Vehicles: Technologies and Challenges" Smart Cities 4, no. 1: 372-404. https://doi.org/10.3390/smartcities4010022

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Power System Resilience: The Role of Electric Vehicles and Social Disparities in Mitigating the US Power Outages

• Loni, Abdolah
• Asadi, Somayeh

Electrical power systems with their components such as generation, network, control and transmission equipment, management systems, and electrical loads are the backbone of modern life. Historical power outages caused by natural disasters or human failures show huge losses to the economy, environment, healthcare, and people's lives. This paper presents a systematic review on three interconnected dimensions of (1) electric power system resilience (2) the electricity supply for/through Electric Vehicles (EVs), and (3) social vulnerability to power outages. This paper contributes to the existing literature and research by highlighting the importance of considering social vulnerability in the context of power system resilience and EVs, providing insights into addressing inequities in access to backup power resources during power outages. This paper first reviews power system resilience focusing on qualitative and quantitative metrics, evaluation methods, and planning and operation-based enhancement strategies for electric power systems during prolonged outages through microgrids, energy storage systems (e.g., battery, power-to-gas, and hydrogen energy storage systems), renewable energy sources, and demand response schemes. In addition, this study contributes to in-depth examination of the evolving role of EVs, as a backup power supply, in enhancing power system resilience by exploring the EV applications such as vehicle-to-home/building, grid-to-vehicle, and vehicle-to-vehicle or the utilization of second life of EV batteries. Transportation electrification has escalated the interdependency of power and transportation sectors, posing challenges during prolonged power outages. Therefore, in the next part, the resilient strategies for providing electricity supply and charging services for EVs are discussed such as deployments of battery swapping technology and mobile battery trucks (MBTs), as well as designing sustainable off-grid charging stations. It offers insights into innovative solutions for ensuring continuous electricity supply for EVs during outages. In the section on social vulnerability to power outages, this paper first reviews the most socioeconomic and demographic indicators involved in the quantification of social vulnerability to power outages. Afterward, the association between energy equity on social vulnerability to power outages is discussed such as inequity in backup power resources and power recovery and restoration. The study examines the existing challenges and research gaps related to the power system resilience, the electric power supply for/through EVs, social vulnerability, and inequity access to resources during extended power outages and proposes potential research directions to address these gaps and build upon future studies.

• Energy equity;
• Electric Vehicle (EV);
• Power outage;
• Power system resilience;
• Renewable energy sources;
• Social vulnerability

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

The Adoption of Electric Vehicles: Challenges and Issues for a Future Research Agenda

Sales of electric vehicles (EVs) grew rapidly in recent years. The vast literature on EV adoption, however, has generated regional, mixed, and sometimes contradictory results. A careful examination of the literature reveals overreliance on quantitative research methods and a dearth of qualitative, exploratory studies. The mixed findings may not stem directly from flaws in research methodology or research design, but rather reflect the inherent nature of the domain being studied. A research agenda in the tradition of qualitative, grounded theory is proposed.

Related Papers

Pawel Bryla

Electric vehicle (EV) disposition may challenge serious environmental issues such as excessive dependence on oil, especially in the transport sector. Despite this understanding, the adoption intention has been disappointing to date. This review tries to present a comprehensive overview of the methodologies, theories, and variables used in 57 peer-reviewed articles published between 2015 and 2022 covering the main forms of consumer adoption of EVs, consisting of purchase as well as behavioral and usage intentions. Governments may stimulate consumer adoption of EVs with exemptions on roadway tolls, convenient access to charging infrastructures, and tax and economic incentives considering energy trading and vehicle sharing. Second, it is important to create intensive awareness revolving around the EV segment. Furthermore, respecting and understanding consumer preferences would also pave the way for the success of EV acceptance. Finally, consumers’ risk–benefit belief while adopting new technology will play a significant role in choosing an EV in the future, while the biggest barriers to adopting EV will be consumers’ lack of confidence in EV performance, safety standard measures, and range per charge.

Transportation Research Part D: Transport and Environment

vedant singh

Edwin Stafford

Can a fully-electric vehicle (EV) serve an on-the-go family's routine of work, shuttling kids, and road trips? Yes, with some grit and optimism! Here's how my family, living in a small Utah college town, incorporated a state-of-the-art EV into our household, illuminating some consumer perspectives on the existing barriers for broader EV adoption and the marketing tasks needed to enable EVs to bridge “the chasm” between early adopters and mainstream buyers.

Indonesian Journal of Electrical Engineering and Computer Science

Thabit Sultan Mohammed

Adaption of hybrid electric vehicles (HEVs) and electric vehicles (EVs) is an important choice that has many positive environmental and economic impacts, where, it helps in reducing exhaust emission, participation in dropping down the amount of noise pollution, and improving the air quality. With these encouraging impacts as well as the reduction in the price of fuel consumption, electric vehicles become at the top of car industry. A study on electric vehicles and their impact on improving the quality of environment is the main motive of this research. Selected theories and factors related to the electric vehicles’ adoption are investigated and analysed. The main factor that led to the spread of electric vehicles is the reliance on electric energy, so it is considered as zero emissions. But there is another effect, which is that these vehicles need continuous electric charging daily, which in turn needs to generate electricity, which leads to environmental pollution indirectly.

International Journal of Economics and Financial Issues

Hatim Loudiyi

Due to political instabilities, limited non-renewable resources and international conflicts, the energy industry has been subject to high volatilities in the last few years. This had negative effects on many developing economies, namely those importing most of their energy needs from other countries (i.e., Morocco). More recently, the high increases in energy prices have renewed interests and discussions related to the adoption of electric vehicles. The current study aims to examine Moroccan consumers’ perceptions and intentions to use electric cars (EV), an era marked by increasing cost of gasoline and other energy sources. Our study proposes an integrated model combining both contextual and technological factors that influence Moroccan consumer’s Perceived value and purchasing intention of electric vehicles. Data was collected using a self-administered questionnaire from 203 Moroccan respondents and the findings were analyzed using the partial least squares (PLS) technique. Our fi...

Benjamin Sovacool

I expand and integrate a theory of mobility (Automobility) with one of science and technology (Actor Network Theory) and one about social acceptance and user adoption (UTAUT). I apply this integrative framework to the diffusion (and non-diffusion) of electric vehicles and the process of electric mobility. I begin by presenting my methods, namely semi-structured qualitative research interviews with social theorists. Then, I present the three theories deemed most relevant by respondents. Automobility holds that, on a cultural or social level, automobiles exist as part of a complex, one that involves hardware and infrastructure-a hybridity between drivers and machines-along with patterns of identity and attitudes about driving pleasure. Actor Network Theory (ANT) involves the concepts of network assemblage , translation, enrollment, and actants and lieutenants. The Unified Theory of Acceptance and Use of Technology, or UTAUT, states that on an individual level, the adoption of new technologies will be predi-cated on interconnected factors such as performance expectancy, effort expectancy, and other facilitating conditions. Based largely on the original interview data supplemented with peer-reviewed studies, I propose a conceptual framework of user acceptance consisting of motile pleasure, sociality, sociotechnical commensurability, and habitual momentum. I conclude with implications for research and policy.

David Rapson

This paper identifies and explores major determinants of electric vehicle (EV) demand in order to inform widely-held aspirations for market growth. We use a simple discrete choice framework to estimate the contribution of intrinsic (no-subsidy) EV demand growth, net-ofsubsidy EV cost declines (e.g. batteries) and government subsidies to future EV market share in the United States from 2020-2035. Geographic variation in preferences for sedans and light trucks highlights the importance of viable EV alternatives to conventional light trucks; belief in climate change is highly correlated with state-level EV adoption patterns; and the first $500 billion in cumulative nationwide EV subsidies is associated a 7-10 percent increase in EV market share in 2035, an effect that diminishes as subsidies increase. The rate of intrinsic demand growth dwarfs the impact of demand-side subsidies, highlighting the importance of efficient allocation of public resources. *(Archsmith) University of Marylan...

Bradley Lane

International Journal for Research in Applied Science and Engineering Technology IJRASET

IJRASET Publication

The advancement of the global economy and technology has developed human civilization to a greater extent, it has also caused Massive damage to the global environment. solar energy, hydrogen fuel, and nuclear power are technically complex and cannot achieve mass production in a short period of time. Electric energy is a feasible energy solution at present, can solve the country's dependence on oil resources to a certain extent. As environment concern increases day by day and introduction of the new BS6 engines in India shows a great step in moving towards creating environment-friendly vehicles. But the problem of moving forwards at this pace in India is about the customer perceptive towards electric vehicles in India. As people are not much aware of the technology is and what is the change that it would bring in to there life and environment around them. We can it can be the lack of knowledge about electric vehicles or the trust that they have on the traditional fossil fuel vehicles. As India is a country with people having different lifestyles, habits, cultures etc…its a tough thing for the government here to quickly shift to electric vehicles. This paper talks exactly about the perceptions and buying behavior of the customer when an electric vehicle is launched in the market. this paper will show us a brief understanding of how people in India have their opinion about owning an electric vehicle and difficulties that they feel which concerns them over buying an electric vehicle over traditional diesel and petrol engine vehicles. So after going through the data that's been collected on this study I was able to find quite a few interesting things that have been affecting consumers buying decision towards electric vehicles not that they are not ready to embrace the new technology that's coming but it's more about the doubtfulness that the people have that can they have this in there society and how much will it impact their society positively and negatively. The study also shows that people are more concerned about its long-lasting feature such limited range as people in India love travelling in there own vehicles and the safety of the car as it runs on a battery which is quite new for the people and its durability. The factors that influences customers in purchasing of electric vehicles are not only about the design and development of electric vehicles that suits customer demands but it also serve as a theoretical idea in which Electric Vehicles can be Maximized and provide a choice for Customers purchase. the government and Automobile manufacturers need to focus on increasing the awareness and give publicity of there electric vehicles and Start launching more attractive battery, infrastructure and charging schemes to attract customers and promote the sustainable Energy development of the automobile industry.

Doina Olaru

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Azita Saeidi

Energy Policy

Tania Del Matto

International Journal of Sustainable Transportation

Steven R Gehrke

THE MAAGEMENT ACCOUNTANT

Sarvesh Rawat

Sustainability

Zulfiqar Lashari

World Electric Vehicle Journal

Vitória Albuquerque

Annals of Operations Research

Ramkrishna Manatkar

Flavia Tsang

Travel Behaviour and Society

Daniel Meskovic

Innovative Marketing

Mohammad Naushad

Smaran Shetty

Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management

Energy Procedia

Chankook Park

Transportation Research Part A: Policy and Practice

Benjamin Gardner

J. Andres Coca-Stefaniak

Moataz Mohamed

Diann Gaalema

Transport Policy

Future Transportation

Fabian Israel

Procedia - Social and Behavioral Sciences

Volodymyr Bilotkach

Journal of Innovation Management

Ranjita Singh

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Advertisement

Routing Problems with Electric and Autonomous Vehicles: Review and Potential for Future Research

• Expository Reviews
• Open access
• Published: 31 May 2023
• Volume 4 , article number  46 , ( 2023 )

Cite this article

You have full access to this open access article

• Themistoklis Stamadianos 1 ,
• Nikolaos A. Kyriakakis 1 ,
• Magdalene Marinaki 1 &
• Yannis Marinakis   ORCID: orcid.org/0000-0002-1989-5815 1  

2685 Accesses

5 Citations

Explore all metrics

The transportation sector has undergone a major transformation in the past few years with the shift to electric mobility and the introduction of new, promising types of vehicles. Sustainability is the driving force of this revolution, but, these changes are expected to greatly impact the space of logistics operations. Electric vans have been in the market for a few years already, and they are comparable to gas-powered vehicles in certain applications; however, they are not the only ones with great potential. Drones and ground robots are two new types of vehicles, the characteristics of which offer remarkable opportunities in supply chains. Nonetheless, theoretical research on logistics operations with the abovementioned vehicles has been distant from reality. This research aims to help researchers explore the untapped potential of electric vehicles. To achieve this, a thorough look into their technical aspects is provided, to determine the key elements that distinguish them, make a comparison to the existing literature, and identify the research gap. Due to the increased complexity and the sensitivity of these vehicles to externalities and uncertainties in general, research should address and explore four major elements of these novel supply chains, energy consumption , new vehicle types , dynamic environment , and communication between vehicles.

Similar content being viewed by others

A Survey of Truck–Drone Routing Problem: Literature Review and Research Prospects

iTRANS: Proactive ITS Based on Drone Technology to Solve Urban Transportation Challenge

Algorithms for Solving the Vehicle Routing Problem with Drones

Avoid common mistakes on your manuscript.

1 Introduction

Modern means of transportation laid the foundation of today’s society. Transportation vastly aided the development of commercial activities and the development of the economy and raised the standard of living of many people around the world. What makes transportation effective and efficient is proper planning, which can be split to two parts, transportation infrastructure and how it is utilized. Infrastructure consists of the networks that connect places, i.e., roads, and supporting utilities such as gas stations. How the above are utilized is what determines the efficiency of transportation.

The research of Dantzig and Ramser [ 1 ] was the first on this issue, presenting the truck dispatching problem and aiming to find the best possible way to deliver fuel to gas stations. Today, we refer to such problems as vehicle routing problems (VRPs). Since its inception, countless variants of VRP, and even more solution methods, have been presented [ 2 ]. By the end of the 1990s, most of the algorithms that are still used today for VRP were already introduced. Despite that, interest in VRP has yet to seize, since the means of transportation and the needs of people keep evolving over time. The latest addition to VRP, which initially emerged out of necessity but has proven to have additional benefits, is the employment of alternative fuel vehicles, namely electric vehicles (EVs) [ 3 ].

EVs have become a prevalent topic of research, both from an operational and a managerial viewpoint. The electric vehicle routing problem (EVRP) has gained a lot of popularity since the presentation of its first variant in [ 4 ]. Although some external parameters that affect the driving range of EVs have been addressed [ 5 ], they often use arbitrary values that do not reflect the conditions encountered in practice by EV drivers and do not represent reality. The objective of this paper is to address this gap by providing researchers with valuable information and future research directions that bridge the gap between theoretical research and the actual characteristics and abilities of all EVs. This will enable more accurate and effective solutions to be developed for the EVRP, which is crucial for promoting the wider adoption of EVs, reducing their environmental impact, and getting the most value out of them.

1.1 Sustainability and Electric Vehicles

Sustainable transportation is a global goal in the field of logistics and the use of EVs is one of the methods that will assist in achieving this goal. By prioritizing sustainability and making it a core part of the business strategy, logistics companies can help to mitigate the negative impacts of transportation on the environment and promote long-term economic and social sustainability [ 6 ]. By adopting sustainable practices and behaviors, logistics companies can help to create a more sustainable and efficient supply chain that benefits all stakeholders, including the environment, consumers, and the economy [ 7 ].

The EV space contains a plethora of vehicles, of different kinds and with different technologies. The types of vehicles solely equipped with electric powertrains can range from two-wheeled electric-assisted pedal bikes to full-fledged electric trucks for logistics operations [ 8 ]. An area of high interest has been the introduction of autonomous vehicles in supply chains, such as drones [ 9 , 10 , 11 ] and ground robots. These vehicles are Internet-of-Things (IoT) devices, which may effortlessly communicate and coordinate with each other, revolutionizing logistics operations as we know them [ 12 , 13 , 14 ].

Each type of vehicle has its own unique advantages and limitations, and thus, should be utilized accordingly within supply chains. For example, flying drones are not bounded by traffic congestion, but have a low payload capacity. In contrast, ground robots have the ability to carry heavier items, but are bound to the road network. In combination, the strengths of each vehicle type can be leveraged as required. Overall, by correctly integrating these novel vehicles, supply chains become more effective and efficient, both financially and environmentally. Their autonomous nature and their ability to cooperate as a swarm has the potential to make operations more agile, and adaptive, with significant improvements in the quality of service.

1.2 Related Research

Given the popularity on the subject of EVs, there have been recent publications reviewing and discussing their application in VRP [ 5 , 15 ]. Other publications on EV adoption [ 16 , 17 , 18 ] discuss the topic from a managerial and strategic standpoint while this research provides an in-depth analysis of the technical characteristics that affect the integration of electric-powered vehicles in the supply chain.

Drones and robots on the other hand belong to the class of autonomous vehicles. While they can be manually operated, when used in logistics operations, they are expected to be fully autonomous. Since fully autonomous drones are already in use for commercial deliveries; it is not a far-fetched assumption. In [ 19 ], the authors explore different classification criteria for drone routing problems and path planning problems and provide an overview of existing literature on the topic. A broader look into the potential use cases for drones was presented in [ 20 ], with both social and technical impacts being discussed. In [ 21 ], the need for advanced data management and policy frameworks during the transition phase is discussed, while in [ 22 ] the focus of the study is on fully autonomous vehicles and their impact on private and public transportation. In [ 23 ], the use of autonomous mobile robots for intra-logistics applications is discussed. Another relevant review is the one presented in [ 24 ], which discusses both drones and robots in two-echelon applications, however, once again from the traveling salesman problem (TSP) and VRP perspective.

In contrast to these publications, this research is not focused on reviewing the existing literature on the EVRP. Instead, the purpose of this study is to provide an overview of the current approaches in the literature on the subject of routing battery EVs, along with literature presenting EV experiments in the real world. This is motivated by the gap between the practical experiments and the computational studies. The authors aim to provide both a good understanding of the unique characteristics and the technical aspects of the new types of vehicles, to present existing approaches in the literature, to identify important elements to be explored and addressed in future research, and to provoke new ideas and concepts that help with their adoption.

1.3 Research Methodology

The survey aims to highlight the discrepancy between the hard technical characteristics of EVs, including autonomous robotic EVs, and the approaches in the literature utilizing them and suggest future research directions. Therefore, the publications included are not limited to specific types of VRPs, but represent a wide spectrum of their applications and perspectives. The research is structured in the following way; first, the technical characteristics of EVs, and their published applications, are analyzed and discussed. Secondly, the research is expanded to include publications that utilize autonomous robotic vehicles, in tandem with EVs, extending the capabilities of both vehicle types.

The term EV can be used to describe a wide range of vehicles that use electric motors for propulsion, i.e., battery-powered EVs, hydrogen fuel-cell EVs, plug-in hybrids [ 25 ], and EVs with range-extending ICEs [ 26 ]. Each EV type has unique features that offer different advantages and disadvantages. This research is concerned with the most heavily constrained type, the battery-powered EVs.

To define the level of realism in EVRP research, a systematic review was conducted. Science Direct and Google Scholar were the two databases used to find relevant literature. The keywords used to find relevant research and review articles were “Electric Vehicle Routing Problem,” “EVRP,” “Vehicle Routing Problem with Drones,” and “Vehicle Routing Problem with Robots.”

The recently published review articles on EVRP [ 5 , 15 ] were thoroughly studied to determine the current trends and the missing link between theoretical studies and real-world applications. The research papers included in EVRP reviews are mostly variants of VRP updated to employ EVs instead of traditional vans and trucks. It was found that although all review papers discuss the need for a more realistic representation of the real world, they do not mention any of the existing work regarding EVs outside of the theoretical research on EVRP.

Retrieving and reviewing all available research articles would be an impossible task; therefore, the research papers on EVRP that focus on parameters of interest were selected to be included in this paper, as parameters of interest are considered those that can be measured or predicted within a certain degree of accuracy, and used to calculate the energy consumption. Besides EVRP, general research regarding EVs was also considered. The research papers regarding EVs that were of interest are those that carried out tests, either in a lab environment or in real-world conditions, as well as papers discussing the viability of transitioning to purely electric vehicles or electric vans and trucks in case of commercial and industrial use cases. These papers were acquired by targeted research on the same platforms as before.

Charging infrastructure and its effect on EVs is also discussed; however, infrastructure development is not discussed as it is a separate issue from a technical standpoint. Nonetheless, charging technology and the different charging behavior of different EVs is showcased with the intent of highlighting the importance of case-specific problem-solving for EVRP. Indicative EVRP research papers that have considered different charging technologies have been included in the review.

The contribution of this research can be summarized to the three following points:

To present the range of VRP variants found in the literature utilizing these novel means of transport, describe the technical characteristics of those and their individual strengths and weaknesses, and explore the different ways they have been combined so far.

To highlight the limitations of the recent VRP approaches found in the literature, the oversimplification over real-life applications, their static nature, and lack of uncertainty which would make them inapplicable in practice.

To suggest a direction towards which the VRP research should focus, based on the current state-of-the-art means and their potential as IoT devices within a network of interconnected cooperative vehicles.

The structure of this research paper is the following: Sect.  2 provides the state of the art of electric vehicles and their technology, an assessment of the level of realism in the EVRPs, and raise concern on the related issues. In Section 3 , technical information, strengths, weaknesses, opportunities, and threats, along with key literature references are provided for drones and robots. Section  4  raises questions based on the findings of the study and proposes future research directions. Finally, Sect.  5 presents the conclusions of the research.

2 Electric Vehicles and Logistics

Initially, this section provides a very short reference to the history of EVs, along with a comprehensive list of their most important strengths and weaknesses. An assessment of the realism level of the EVRP literature follows, and information regarding the energy consumption and charging, and parameters that affect them are discussed. A short technical overview of the currently available electric vans is presented as well.

2.1 Short History of Electric Vehicles

In the early 1900s, out of the 4200 vehicles registered in the USA, about \(40\%\) of which were steam-powered, another \(40\%\) was electric-powered, and the rest were gasoline-powered [ 27 ]. EVs were easier to operate compared to the gasoline-powered vehicles of the time. The Electric Vehicle Company was the biggest automotive manufacturer of the time, in the USA. Their business model was based on renting the vehicles for the day and taking them back for overnight charging and any necessary maintenance, a business model that has started once again to gain popularity. The company fell into some legal trouble and eventually went out of business. At the same time, the Ford Motor Company started the production of the highly successful Model T, which led to the demise of the EV once and for all [ 28 ]. In the 1990s, General Motors allegedly self-sabotaged their own EV attempt, in favor of keeping their business model intact. The first commercially successful EV arrived in 2012 by Tesla. It was the first EV that could directly compete with the internal combustion engine (ICE) vehicles in terms of driving range and was proof that EVs can be an option [ 29 ].

2.2 Strengths and Weaknesses of Electric Vehicles

A description of the main strengths and weaknesses of EVs is given in the following list. They are not presented in any particular order.

Running costs: The cost per unit of distance is usually lower for EVs compared to ICE vehicles, since electricity will in general be cheaper than gasoline or diesel [ 30 ].

Maintenance costs: EVs are mechanically simple compared to ICE vehicles. The average electric powertrain contains just a fraction of parts compared to modern ICEs [ 31 ].

Preferable for urban logistics: Given their zero tailpipe emissions and the lack of noise, EVs are perfect for urban applications [ 32 ].

Incentives: There are currently incentives in many countries across the world for potential EV buyers, such as tax reliefs, subsidization, and other [ 33 ].

Weaknesses:

Range: It is one of the first points of worry for anyone looking to buy one. In the case of electric vans, Mercedes-Benz has published that after analyzing 1.6 million EV trips, almost all no longer than 100km [ 34 ], which is within the capabilities of the currently available vans.

Payload: The payload of EVs is a parameter that has a direct effect on range. Any vehicle with a payload will require extra energy to move compared to it being empty, given the extra inertia. It should be noted that EVs usually have a lower maximum payload rating compared to ICE vans [ 35 ].

Charging: The speed of charging and the available infrastructure is another point of worry. Charging stations and especially fast-chargers are not so common, yet [ 36 ].

Cost: While some costs associated with EVs are lower compared to ICE vehicles, the initial cost of purchase is more often noticeably higher than that of conventional ICE vehicles [ 37 ].

2.3 Assessing the Level of Realism in EVRPs

This section aims to compare the real world to the existing literature on EVRP. Charging and discharging are the main issues to be discussed, as they are very important for a realistic VRP. There are a few critical technical aspects of EVs that are usually not considered in EVRP studies and affect both charging and discharging. In practice, many parameters must be concurrently addressed, many of which are interdependent. The most recognizable are vehicle payload and speed, temperature, use of auxiliary devices (i.e., air conditioning), driving characteristics, the current state of charge (SoC), and energy losses (drag, tarmac friction, etc.).

Some of these have been studied both in real life and in the EVRP literature, and are presented in the following paragraphs.

2.3.1 Temperature

Temperature is a very influential factor of EV general operation. For example, using an EV in colder climates has an effect on the efficiency of the battery, while it necessitates the use of heating elements for the occupants of the cabin, leading to further energy depletion. The optimal battery operating temperature typically ranges from \(22\) to 25 °C, depending on the vehicle [ 38 ]. During the summer, charging can become slower as a result if the vehicle cannot maintain a low enough temperature during charging. Temperature does not affect battery performance only during charging, it is highly important during discharging too, especially when vehicles are parked outside, and exposed to the elements. Cold operating conditions can also have an effect on battery aging [ 39 ]. Normal driving does not really heat up the battery of the EV; therefore, extra measures do not need to be taken to bring the batteries to operating temperature. In [ 40 ], a graph of energy consumption throughout the year, as temperatures change, shows the effect temperature had on the range of a Nissan Leaf EV. Furthermore, using the EV within city limits at temperatures lower than 15 °C resulted in a poor range. In [ 41 ], the authors focused on battery degradation for lithium iron phosphate batteries. One of the tests they performed showcased the battery capacity loss against the charging cycles for three different temperatures, for three different depths of discharge. While the tests were performed in lab conditions and not used in actual vehicles, the results might not exactly coincide with real-world tests, but, they prove that both the depth of discharge and the operating temperature may affect the longevity of batteries. In reality, the depth of discharge may not be an overall issue, given the battery controller spreads the demand across all battery cells.

2.3.2 State of Charge

The SoC of the vehicle is a very critical parameter for charging as well. The demand profile of an EV battery was studied in [ 42 ]. The results of their tests suggest that the SoC should be in the range of \(20\%\) to at most \(90\%\) . Their validation experiment showed a linearity in battery voltage between \(20\) and \(80\%\) for a constant current value, both during charging and discharging. In [ 43 ], the researchers focused on finding the best charging scenarios for EVs. They also presented a lot of relevant literature on the subject of EV charging. They suggest a similar SoC window of operation for EVs, between \(20\) and \(80\%\) .

2.3.3 Consideration of Realistic Parameters in EVRPs

Most of the EVRP literature, especially earlier studies, used very simplified, linear energy consumption models. Later studies started to introduce elements of realism in their models, i.e., weather conditions or vehicle speed; however, there still is a lot of room for improvement.

The energy consumption functions used in the literature have not been related to any existing vehicles, with the exception of those that use some characteristics of passenger EVs. The problem with that tactic is that the most important factor, weight, is not accounted for. Some noteworthy studies that tend towards a realistic energy consumption estimation are the following. An EVRP considering the effect that vehicle load would have on the battery was carried on real-life data from Austin, TX [ 44 ]. In [ 45 ], a new formula was developed for energy consumption, taking into account speed and weight. They tested the performance of their hybrid genetic algorithm on a Beijing road network. An EVRP with time windows (EVRPTW) was solved in [ 46 ], considering the energy consumption rate as a function of speed and weight. In [ 47 ], the EVRP was solved using an ant colony optimization algorithm and an adaptive large neighborhood search (ALNS) algorithm, aiming to minimize energy consumption instead of distance traveled, to prove it is a superior tactic. To calculate the energy, the weight, speed, and road friction were considered. In [ 48 ], an energy consumption model that considers the topography and the speed profiles was developed. First, the road network is evaluated and, then, the two-stage approach seeks the solution. The experiments were carried out on a Swedish road network. The effect that ambient temperature could have on vehicle routing was considered in [ 49 ], given the need for a tolerable cabin temperature and the fact that EVs are less efficient in cold environments. Their objectives were the minimization of the fleet size and the minimization of total energy consumption. They used passenger EVs and, therefore, there may be inaccuracies when compared to electric vans. In [ 5 ], a very detailed literature review was presented along with a new model for EVRPTW. The energy consumption rate of the new formulation is the richest to date, accounting for aerodynamic, tire, drivetrain, ancillary, and other energy losses. Another recent addition is the work presented in [ 50 ]. The authors presented a problem in which the distance the vehicles have to travel is not too long; subsequently, charging is not an issue. An extensive analysis was carried out on case studies of four cities to demonstrate the sensitivity of the parameters of the problem. These parameters were the capacity, the max travel time, the service time, and the range of the EVs.

2.3.4 Charging Infrastructure

The terminology for charging stations is electric vehicle supply equipment; however, in this research, they are referred to as chargers or charging stations, since they are commonly referred to as such.

Currently, no universal standards exist on charging speeds or charging ports. Charging can be categorized into two types, alternating current (AC) charging and directional current (DC) charging. AC is typically used for most traditional slow chargers, while fast chargers are more often than not of the DC type. DC charging bypasses the AC-to-DC converter of the vehicle and directly charges the battery, making charging even more efficient. Each current type may be divided into two levels, depending on the region. North America, Europe, China, and Japan have adopted four different charging port standards. Further insights into the charging speeds and technology standards are provided in [ 51 ] and in [ 52 ].

There are two different aspects of charging to consider. The first one is whether charging is full or partial. As stated previously, the SoC has to be maintained below a certain percentage to extend the life of the battery. Partial recharging (PR) has already been implemented and suggested by many researchers in the field of EVRP. In [ 53 ], four different cases of EVRPTW were solved, each with a different charging limitation, and concluded that allowing PR, as many times as necessary, is the best approach. [ 54 ] solved the EVRP with PR while considering charging parameters such as time-dependent energy pricing and the efficiency of the EV’s energy converter. In [ 55 ], a three-phase mat-heuristic was introduced for the time-effective EVRP with PR, aiming to minimize the number of EVs used and the total time. In [ 56 ], the authors considered the limited charging capacity of charging stations and explored PR strategies to improve charging times. In [ 57 ], an EVRPTW was solved, showing the advantages of quick charging in route planning compared to a single charging policy that leads to a reduction in cost and fleet size.

The other aspect is the charging profile. Each EV has different components, which means that the charging characteristics are not universally the same. In Fig.  1 , the charging profiles of four EVs are presented to showcase the diversity of charging profiles among EVs. The Tesla Model 3 and the Renault Zoe are the only two vehicles with a charging curve that has an almost linear behavior. On the other hand, the DS3 e-tense charging curve resembles a stepped line graph and the Porsche Taycan 4 s charged at about 250kW up to \(45\%\) and then the charging speed linearly drops until about \(75\%\) . Charging curves change significantly outside of the bounds of the graphs, meaning before \(10\%\) and after \(80\%\) charging takes place slower to avoid damaging the components of the EV. In literature, non-linear charging profiles have already been proposed. An EVRPTW was solved in [ 58 ], utilizing a different model and a concave non-linear charging function with the objective of minimizing the total operational costs. In [ 59 ], a nonlinear charging function was considered along with limited capacity charging stations when solving EVRP. A two-layer genetic algorithm was presented in [ 60 ] for solving EVRPTW with multiple depots and partial, non-linear recharging. In [ 61 ], a lot of attention was paid to the battery and the effect that the depth of discharge would have on the life of the battery. They suggest maintaining a high SoC, as expected. The issue with the non-linear functions currently found in literature is that they do not represent any existing vehicles.

Examples of different charging curves

2.3.5 Fast Charging

Being able to fast-charge a vehicle is critical in logistics operations [ 62 ]. Refueling for ICE vehicles is never thought of as an issue, as there are plenty of gas stations that can quickly refill the tank that will suffice for all-day use, on most occasions. While in [ 63 ] it is suggested that fast charging will lead to battery degradation, fast charging is in many cases inevitable. Fast charging makes the battery heat up due to the quick surge of energy. Manufacturers are aware of the related issues and in most cases, vehicles equipped with fast-charging capabilities are, also, equipped with battery liquid cooling or other technologies that help minimize the long-term side effects of extreme temperatures.

Fast charging has not been researched extensively in EVRP, yet [ 57 , 64 , 65 ]. Nonetheless, all research indicates the benefits of fast charging on logistics operations.

2.3.6 Battery Swapping

Battery swaps have also been researched, but they are not generally applicable to electric vans, as their large batteries cannot be swapped easily. In [ 66 ], the EVRPTW with synchronized mobile battery swapping (SMBS) was introduced. An EV can request a battery swap on the fly. A battery swap vehicle drives to the meeting point the driver of the EV requested, to make the battery swap. This method of replenishing energy is proposed to alleviate range anxiety. They tested SMBS against traditional charging stations, which they estimate to cost about 3.9 times more. A two-echelon EVRP but with battery swapping stations instead of traditional charging stations was solved in [ 67 ]. In [ 68 ], a variant of EVRP was presented, combining recharging and battery swapping. More specifically, EVs can recharge during their trips or swap their batteries in specific locations, with the help of battery-swapping vans, meaning two VRPs have to be solved at the same time.

2.4 Technical Overview of Existing Electric Vans

This section aims to provide researchers with a basic overview of electric vans and purpose-built electric vehicles for urban logistics applications. Most of the instances used in EVRP are several decades old. The purpose they serve is algorithm comparisons. There is a need to create instances of realistic characteristics that can provide insights for real applications. To help researchers achieve that, basic information, such as the vehicle range and how it is measured, payload capacity, and charging speeds for existing vehicles used currently for urban deliveries, are presented.

Battery technology is the most important factor impacting the adoption of EVs. Vast amounts of resources are devoted to research and development. Modern EV batteries are of the lithium-ion type [ 69 ]. A lot of small-size batteries are glued together in series or in parallel and together they form the battery of the vehicle. In the case of a modern Tesla, more than 7000 small batteries are used. Their energy capacity is measured in kilowatt-hours (kWh).

EV efficiency from tank to wheel, meaning from the battery, through the electric motor, to the wheels is very high. ICE vehicles have a value ranging from \(0\%\) when idle to a maximum of \(20\%\) at the optimal engine rotation speed (rounds per minute or rpm) and operating conditions. EVs can achieve a tank-to-wheel efficiency of more than \(90\%\) regardless of the speed of the vehicle [ 70 ]. This is partly owed to the lack of the ICE and party due to the simple, single-gear, transmission mechanics.

On the other hand, contemporary EV batteries have not yet achieved the same energy density as petroleum products. More specifically, diesel fuel has a specific energy value of 45MJ/kg, and one of the most popular EVs, the Tesla Model 3, has less than 0.5MJ/kg. Therefore, to achieve a usable driving range, battery packs tend to be heavy, accounting for as much as a quarter of the total vehicle weight. For freight vehicles, this is especially bad, since a heavier battery pack lowers the maximum payload capacity of the vehicle.

Electric van battery capacities may range from 37.3kWh for a VW ABT e-Transoporter, able to provide 132km of driving range according to the Worldwide Harmonized Light Vehicle Test Procedure (WLTP). On the other end of the spectrum, the Toyota Proace Electric may be equipped with a 75-kWh battery providing an extra 200km of range compared to the Volkswagen, at 330km, according to WLTP. In the WLTP, the vehicles are tested with \(15\%\) of their rated payload. Still, according to manufacturers and researchers, in most cases, vans do not cover distances greater than the WLTP range of the electric vans found today on the market [ 34 , 71 ].

Table 1 presents a few electric vans appropriate for different kinds of logistics operations. They range from commercial hatchbacks, like the Renault Zoe Commercial, to the electric variant of the Sprinter from Mercedes-Benz. The table contains the model names, the battery capacity in kilowatt-hours, the range in kilometers, the maximum payload in kilograms, and cargo volume in cubic meters, along with the estimates of the manufacturers for the charging time given a charging station able to provide the maximum single-phase AC charging by European standards. In some cases, more than one battery option was available. An odd feature is that the larger Fiat E-Ducato and Mercedes eSprinter when equipped with the large battery pack option have a lower maximum payload. This is necessary in order to keep the gross weight below 3.5 metric tons of weight, given that larger batteries weigh more. The reported range values are the WLTP combined use ( \(55\%\) urban and \(45\%\) extra-urban) test results.

The WLTP test is carried out under controlled laboratory conditions and consists of four different phases, including low- and high-speed driving, and a combined cycle test that simulates urban and highway driving conditions. The test vehicle is equipped with a standard set of sensors and measuring devices. The test is performed according to a standardized driving profile, which takes into account various factors such as vehicle weight, engine power, and aerodynamic resistance. According to the WLTP technical regulations, the temperature is set at 23 °C and 14 °C. The type, pressure, size, and condition of the tires used in the test are also monitored since tires are a critical factor in energy consumption. One of the missing elements is wind speed, which could affect the range of an EV when traveling at highway speeds. The exact details on the procedure followed can be found in [ 72 ].

It is evident that the best-valued vehicles are small- and medium-sized vehicles (based on the cargo volume), depending on the use case. However, it could be argued that unless the weather conditions are harsh, vehicles such as the Renault Zoe Commercial could be replaced by a trike or other, more energy-efficient vehicles compared to the Zoe. Furthermore, the two largest vehicles would be suitable for applications where light items of big dimensions have to be transported.

In contrast to the vehicles of Table 1 , new companies and start-ups that have focused on EVs strictly developed for urban logistics are even more interesting. While bigger companies have already invested millions in research, development, and tooling for ICE vehicles and try to adapt them to electric power plants to maintain their economies of scale, small companies produce purpose-built vehicles from scratch that do not have to fit into any existing standards. Offerings from Melex (Poland), ALKE (Italy), Paxster (Norway), and others have presented many vehicles in this segment. Table 2 presents the technical specification for some of these vehicles. The model, battery capacity, range, max payload, cargo volume, and max speed are reported for each vehicle according to the manufacturers’ websites. The Paxster L6e has two cargo compartments, one in the front and one in the back. The Melex 3 and the ALKE ATX320E are quite similar, while the ALKE ATX340E offers a greater battery size and greater payload and range.

3 Drones and Robots in Logistics

The current limitations of EVs, such as their range restrictions and dependence on charging infrastructure, pose significant challenges to their widespread deployment. One of the best ways to enhance the reach of EVs without the need for larger batteries, frequent visits to charging stations, or the need for a breakthrough in battery technology, is to combine them with autonomous vehicles such as drones and robots, offering a promising solution to the current limitations of EVs.

Furthermore, this integration has the potential to unlock new and innovative use cases for EVs, providing additional value to stakeholders, such as fleet operators, consumers, and the environment. In this light, the combination of EVs with drones and robots is a promising area for future research and development, with significant potential for advancing the deployment and utilization of EVs in a variety of domains.

The following subsections provide a comprehensive view of the various research paths already discovered within the scope of VRP, along with some indicative examples from real drones and robots. Although many researchers have opted to use them independently, in the context of deliveries, the most realistic application is the use of EVs as mobile depots for these vehicles.

One of the most popular means of transporting parcels in the recent VRP literature is drones. Their popularity rose in the past 5 years, since well-known commerce and logistic companies, such as Amazon and DHL, openly started considering them for last-mile deliveries, in an autonomous way.

Drones inherit the environmental benefits of all-electric vehicles, such as the lack of local emissions, but also their drawbacks which is the limited range of operation without requiring recharging. Their maximum payload is another limitation, as the energy required to lift heavy items would make them practically unusable. Moreover, drone operations are very sensitive to weather conditions, as unpredictable factors like wind and rain greatly affect them. Nevertheless, unlike EVs, drones have the ability to overcome obstacles, such as traffic and buildings, making deliveries faster in principle by traveling shorter distances to reach a destination. In [ 10 ], it is suggested that drone and ground vehicle integration in logistics can offer multiple benefits including monetary and environmental.

3.1 Technical Overview of Drones

This subsection discusses the technical characteristics of drones. Table 3 displays the specifications found in the corresponding official websites or estimations of third-party online sources in cases where official values are not publicly available for the most well-known service providers.

Real-life applications are more common than one might think and expand among many different areas. Amazon has been an early adopter of drone deliveries, developing their own drones, capable of carrying payloads of up to 2.25 kg, for trips of 30 min at maximum.

In humanitarian applications, Matternet uses drones to transport test samples and medical necessities, while Zipline created a modular fixed-wing drone to be used in blood bag transportation, in Rwanda, providing significant benefits and saving lives.

Information regarding drone specifications is limited and the available measurements are neither standardized nor confirmed by independent third parties, thus, are not comparable to each other. Subsequently, these characteristics should be seen as rough estimates and their true capabilities remain proprietary knowledge of the companies that developed them.

Most drones are of similar size and have similar capabilities, as they are restricted by the battery weight. Two main variants may be distinguished, fixed-wing, and rotary-wing drones, the latter of which is the most common. In most countries, the main barrier to their use in commercial logistics applications is the strict regulatory framework.

The research presented in [ 77 ] is the only published research based on real data from drone flights, analyzing their energy expenditure and providing insights for their use. The drone used is a commercially available drone suitable for transporting items. The energy consumption was determined to be on average 0.08MJ/km, carrying a payload of 0.5kg. Despite the not so wide scope and the limited data used, it is a move in the right direction. The drones were tested against other modes of transportation as well, such as cargo bikes which were also proven to be a very good option in terms of energy expenditure.

3.2 VRPs with Drones

Research on the subject of VRP with drones (VRPD) and its variants is a very recent addition to the literature. The first problem of its kind utilizing drones was introduced in [ 78 ], more specifically the traveling salesman problem with a flying sidekick (FSTSP). In this simple integration of the two vehicle types, the drone is an assistant to the road vehicle. The FSTSP formulation was extended to include multiple TSP with drones [ 79 ]. A recent addition to the TSP with drones was presented in [ 80 ], with the speed of the drone being determined by the weight of the packages it is carrying, similar to the work presented in [ 81 ]. The first research to address the VRPD is [ 82 ], presenting the first formulation of the problem, assuming identical travel speeds for both types of vehicles, which does not realistically reflect the drones’ capabilities. A maximum coverage problem with drones was presented in [ 83 ]. In [ 84 ], a generalized approach was proposed considering VRP with transportable resources, including drones. In [ 85 ], the authors presented a set-covering problem for instant deliveries and look for the best drone take-off locations. They minimized both the number of vehicles and the makespan. In [ 35 ], the novel electric VRP with drones was introduced, minimizing the energy consumption of both types of vehicles, while considering the weight.

There has been great diversity in the concepts and the scenarios researchers have presented. Routing two different types of vehicles bears many difficulties in terms of synchronization. The authors in [ 86 ] addressed separately the truck and drone path planning and then proceed to jointly optimize them. In [ 87 ], a movement synchronization VRP was proposed, applicable to other types of vehicles too. In [ 88 ], a more realistic formulation was presented as drones are transported by trucks (serving as depots and battery swapping stations) and can make multiple deliveries, allowed to return to any station, making many trips if necessary. In [ 89 ], the authors set to lower the customer waiting time. They allocated multiple drones per truck and conduct a case study. In [ 90 ], only drones were allowed to make deliveries to customers while the trucks transport them to the designated launch/retrieval locations. Both in [ 79 ] and in [ 91 ], two-echelon approaches in drone integration were proposed, using the trucks as mobile depots, with the latter allowing direct drone deliveries from the depot too. In [ 92 ], drones and trucks were routed independently, with drones making only a single delivery each time.

Just like EVs, there are a number of factors that may have an implication on the logistics operations with drones. In [ 93 ], the height of the delivery and its effects on the routing operation were considered. In [ 94 ], a more realistic drone delivery system was introduced, as it considered no-fly zones and wind conditions. They assume that rooftops of city buildings may be charging points. In [ 95 ], the problem emphasized weather impact and included collision avoidance as well.

Some applications that may benefit from the use of drones have also been proposed. A dynamic VRP for food delivery application was solved in [ 96 ]. In [ 97 ], the intent is to select the optimal hub for delivering essentials in disaster relief scenarios to best serve those in need and present a theoretical example.

Energy consumption is a very important parameter for drones as well. In [ 98 ], non-linear and linear energy functions were compared while also considering the weight parameter, giving emphasis on the energy consumption.

There are several review papers on drone routing problems in the literature. In [ 99 ], the authors highlight that routing problems with drone integration are an emerging branch of research. In [ 100 ], the review focuses on routing problems with drones, reviewing the existing TSPs and VRPs. [ 101 ] includes in their review a comprehensive list of the recent literature concerning drone integration in multiple TSPs. In the review paper [ 102 ], a drone problem taxonomy is proposed along with a discussion on practical applications. In [ 24 ], the drone integration problem is reviewed from a two-echelon perspective. They provide insights on issues encountered and concentrate on modeling perspectives. Finally, in [ 103 ], the factors that impede real-world applications are discussed and the related research gaps are highlighted.

Although drones are robots and often in literature they are considered as such, it is useful to address them separately in logistics operations given their different properties. In this paper, robots are considered the ground vehicle equivalent of drones.

Similarly to drones, the main application for robots in logistics has, for the greater part, been urban deliveries. Drones and robots share both advantages and disadvantages. They both have zero local emissions, can operate with some degree of autonomy, and are quite versatile, but, they both suffer from a limited operating range. Nonetheless, robots have some unique traits that cannot be matched by drones, like carrying heavy and sizeable items and the ability to operate under harsher conditions, since they operate on the ground and are less affected by wind, and rain. In contrast to drones, robots cannot make deliveries at altitude (i.e., balconies and rooftops) and are bound to follow roads or sidewalks (depending on the size of the robot), traveling longer distances compared to drones. Last and not least, operating on the ground makes them more vulnerable to stealing or other sabotaging efforts.

The VRP variants with robots found in the literature have many assumptions in common, as listed below.

Instantaneous deployment and retrieval times

Fixed operational time independent of the payload or speed

A static, perfect-conditioned environment of operation.

Overall, a combination of drones and robots might bear the most benefits, as their joined strengths could outweigh their individual drawbacks.

3.3 Technical Overview of Robots

It is useful to provide a comprehensive presentation of the capabilities of the robots currently available and discuss their technical characteristics. Table 4 displays the values found in the corresponding official websites or estimations of third-party online sources in cases where official values are not publicly available. There are more robot vehicle models being developed and tested but since no specifications of any kind are available, they have been omitted.

Robots come in many sizes, ranging from smaller ones intended only for sidewalk use to larger ones that could potentially use the streets. The wide range of available robots makes them a versatile vehicle type, able to meet the requirements of practical applications. To make the use of robots in logistics operations more common, two separate issues have to be addressed. First, the technologies related to their use must be improved, mostly with respect to autonomous operations, and secondly, laws and regulations regarding their use have to be set in place. In Fig.  2 , four of the robots from Table 4 are displayed.

KiwiBot (top-left), Amazon Scout (top-right), Starship (bottom-left), Nuro R2 (bottom-right)

3.4 VRPs with Robots

From an academic perspective, the proposed VRPs with robots found in the literature can be grouped based on three criteria that emphasize their major differences. These criteria were chosen as these choices alter, not only certain constraints or the objective but the entire underlying practical application. The criteria are the following:

Customer delivery vehicle: This determines whether only the robots (R) or both (B) types of vehicles are allowed to deliver the packages to the customer locations.

Robot deployment: Robots may be deployed from designated locations (DL), full-fledged robot depots (RD) with storage/recharging capabilities, or only at customer locations (CL).

Robot transportation: This characteristic indicates whether the robots are transported by the truck(s) to/from the deployment locations (Yes) or not (No).

3.4.1 Customer Delivery Vehicle

Models that allow only robots to make deliveries to customers represent the use of robots in the last-mile delivery context. This is aligned with the efforts to reduce emissions, as the bigger multi-ton trucks do not have to move from customer to customer themselves. These models work great when delivering packages of insignificant weight; however, it proves problematic when there are packages that have to be delivered by the truck itself. In practice, this model cannot work in solidarity. Using both trucks and robots for deliveries is a far better option, not only for the mentioned reasons but when controlled substances or age-restricted items have to be transported.

Moreover, when employing both types of vehicles from deliveries, more flexible models that require a lesser degree of synchronization can be explored, depending on the available resources. A scenario of employing trucks as mobile robot depots which deploy robots at customer locations was the first to be proposed. Another scenario is the completely separate routing of trucks and robots, by having dedicated robot depots, a concept that does not require the same level of synchronization.

3.4.2 Robot Deployment

The choice of robot deployment approach significantly affects both the complexity of the problem and its effectiveness. Using designated locations for robot deployment is a realistic and low-cost approach. Despite the lack of storage or charging options, robots may be deployed from such places while trucks continue on their route, and robots may return there at the end of their route and await retrieval. By developing designated robot depots, robots become less dependent on other vehicles, both in terms of synchronization and in terms of charging, since they would be able to recharge on their own. In case deliveries are performed only by robots (that are not moved by trucks), then the problem becomes two-echelon, meaning, there are two separate levels of routing. When customer locations are the only place of possible deployment and retrieval, it is described as a mixed customer delivery approach. This application is arguably the easiest to implement since the robots are used as sidekicks to the trucks and there is no need for any kind of infrastructure; however, it would only be effective if there are multiple customers in close proximity.

3.4.3 Robot Transportation

Most approaches found in the literature use trucks to transfer both the parcels and the robots. The main advantage of this concept is that it does not require significant infrastructure. Thus, it would make financial sense to adopt this approach when operating in a suburban neighborhood, where robot depots capable of having their own robot fleet might not be cost-effective to maintain.

In contrast, when operating in a densely populated urban environment, having robot depots with permanent robot fleets will free important space in the truck which would otherwise be occupied by the robots. If a certain robot depot requires more robots, those could be transported from one to another, given that the robots used in that application can be transported by a van.

Table 5 provides a comprehensive summary of the various VRPs that incorporate robots, as reported in the literature. The first column lists the relevant publications, while the second column specifies the types of vehicles that make deliveries. The third column outlines whether or not the robots are transported by the EVs. The fourth column presents the delivery scheme of the robots’ operations. The subsequent two columns indicate the objective of the studies and the availability of a mathematical model, if any. The final two columns present the solution approach adopted and the number of trucks utilized, respectively.

4 Future Research Directions

In recent years, the EVRP has gained significant attention due to the increasing interest in sustainable transportation. While several studies have addressed the EVRP, there are several potential extensions that could improve the problem’s practical relevance. EVs are often marketed and sold as high-tech products, with a focus on their technological advancements, performance capabilities, and connectivity features. The growing trend of smart mobility and the Internet of Things (IoT) have further enhanced the tech components of EVs. By integrating EVs with connected services such as navigation, charging stations, and energy management systems, the vehicles become part of a broader ecosystem of connected devices and services. Furthermore, they are equipped with a variety of sensors and electronic components that generate a wealth of data, which can be analyzed to gain insights into vehicle performance, energy consumption, and user behavior. The availability of this data has the potential to revolutionize the way we understand and optimize the use of EVs.

A series of questions can be raised, which have yet to be answered by the ongoing research in the EVRP field:

How can we leverage the communication capabilities of those IoT vehicles to continuously optimize the routing during operation based on their sensing abilities?

How can the fleet of vehicles become a swarm of vehicles, working together, cooperatively in order to complete their operation optimally in an uncertain environment?

How can we mitigate the increased sensitivity to externalities of these vehicles, and thus, the increased risk of failure for the operation, making the supply chain more robust?

The following subsections discuss potential future research directions and research topics that should be researched further.

4.1 Energy Consumption

The energy consumption of battery EVs is the element with the highest effect on logistics operations, and it is the first and most important topic to address.

4.1.1 Payload Weight

As discussed in the previous sections of this study, the payload of an EV greatly affects its range; however, the lack of real data means that approximations should be made for now. The advertised range of EV is that of the WLTP standard, at just \(15\%\) of the total payload. Aggressive reduction in range when EVs are loaded to capacity is a very realistic assumption to be made when heavy payloads are transported.

4.1.2 Vehicle Speed

One of the least researched topics in EVRP is the effect of vehicle speed on energy consumption.

Additionally, different driving conditions, such as highway or city driving, can also have a significant impact on the actual range of an EV, which is not reflected in laboratory testing. Furthermore, more research is needed to understand the energy consumption of EVs over a longer period of time and under different driving conditions.

4.1.3 Stochastic Energy Consumption

An additional step for realistic problem-solving in EVRP is the adoption of a stochastic energy consumption mechanism in all EVRPs. This addition will introduce a very important element of realism that is very representative of the real world and necessary for the development of robust solution methods. The stochastic consumption may represent extreme breaking incidents, extended use of auxiliaries, i.e., when being in a traffic jam, and other unpredictable events that do occur in daily driving but cannot be modeled in another way. A way of implementing this stochastic consumption would be to assume an additional load over a unit of distance.

4.1.4 Charging Curves

Besides energy consumption, EVRP is often concerned with the replenishment of the spent energy. Research in the literature has covered both battery swapping and battery charging. Unfortunately, the lack of standardization and the technical difficulties have not allowed battery swapping to become mainstream. Battery recharging has been the prevalent method used for all large vehicles, such as cars, vans, and trucks. The first EVRP papers that considered recharging assumed a linear charging function, meaning the charging time is proportional to the replenished energy. Later, non-linear charging functions were introduced as well. The charging behavior of some EVs can indeed be assumed to be linear such as Tesla vehicles; however, there are many more different types of charging curves as presented in Fig.  1 . To date, there has been no research exploring a variety of real EV charging curves. Future research can include different charging profiles from existing EVs and compare them to one another to provide insights and find the EVs with the most desirable technological characteristics. This is essential as the optimal routes and charging stops could change significantly among different EVs.

4.1.5 Multi-objective Models

Energy consumption has been the most significant difference introduced in VRP when using EVs. This has made energy consumption be treated as the single most important parameter. Nonetheless, there are many different applications that concurrently have additional objectives to fulfill. Multi-objective approaches have been presented in the EVRP literature; however, there are many opportunities for new research, especially when considering the new vehicle types presented in this study. Developing well-balanced multi-objective approaches is a challenging task; however, they are necessary for certain applications, i.e., when delivering perishable products with an EV, or when a drone is used in a medical emergency situation.

4.1.6 New Benchmark Instances

All variants of EVRP to date have been using benchmark instances adapted from other VRP variants found in the literature. One of the first and necessary steps to have a better chance at depicting the real nature of EVs is to have a better representation of EVs when solving problems and benchmarking solution methods. The present study has provided the basis for the creation of new instances. While the distances to cover do not have to be realistic, using the energy capacity and energy consumption of existing EVs will lead to additional insights when solving these problems. Additionally, benchmark instances would have to be updated to represent real-world values, and energy consumption calculations should include the effects of payload weight.

4.2 New Types of Electric Vehicles

New benchmark instances are a step in the right direction; however, using data from a single EV will not provide the necessary level of realism. To go a step further, new types of EVs must be considered in EVRP.

4.2.1 Small Electric Delivery Vans

The new small-size electric vans presented in Subsection 2.4 have not been used in any EVRP variant so far. The use of smaller vehicles comes with unique challenges. The limited available space offers new research opportunities. EVRP can be extended to include multi-dimensional loading constraints to ensure maximum cargo space utilization. Research in multi-dimensional VRP variants has been very limited; however, it would vastly aid in maximizing the utilization rate of all-electric vans.

Small electric vans, like the ones portrayed in Fig.  3 , have become the prevalent mean of urban deliveries in many European cities. Addressing their use can provide insights into their use and abilities.

Paxster EV — source: https://paxster.no (left), ALKE refrigerated EV — source: https://www.alke.com (right)

4.2.2 Heterogeneous Fleets

Despite the widespread use of small EVs in Europe, each market and each business have different transportation needs. Using EVs of different sizes and capacities can provide logistics companies with more flexibility in their operations. Smaller EVs can be used for last-mile deliveries, while larger EVs can be used for longer hauls. Each company has different transportation needs. By using the right size of EV, logistics companies can improve their efficiency and reduce their costs.

Smaller EVs can be used for smaller deliveries, reducing the need to use larger vehicles that may be underutilized. This can result in lower operational costs and reduced energy use. In addition, using smaller EVs for last-mile deliveries can help to reduce congestion in urban areas. These vehicles can be more maneuverable and able to navigate through congested streets more easily, reducing the time spent in traffic and improving delivery times.

Optimizing the fleet composition can have monetary benefits as well. First and foremost, battery size is directly related to the cost of the vehicle, as the batteries are generally the most costly component. Small EVs use small batteries and generally cost less. Regular-size electric vans come with batteries of different sizes. If a business has low range demand, they can select an electric van with a smaller battery and save on the initial cost of the fleet. Subsequently, the fleet composition can have a substantial effect on purchasing costs without sacrificing their operational capabilities.

Publications on the mixed-fleet EVRP have been limited. Researchers can enrich it by using vehicle data representative of the real world, with different charging curves for different types of vehicles and different battery sizes for the same vehicles. Furthermore, it is worth exploring different operational scenarios in regard to charging policies for each type of vehicle. Given the variety of EVs available today and the mentioned potential benefits, the use of heterogeneous EV fleets should be researched further to provide insights for real-world applications.

4.2.3 Multi-echelon Approaches

One of the most efficient methods used to dissect the delivery operations when multiple delivery stages are involved is using multiple echelons. Traditionally, multi-echelon problems refer to scenarios where there are multiple levels of distribution centers or warehouses that need to be serviced by a fleet of vehicles. Frequently, each echelon has different vehicles. However, this scheme can be used to represent a system of interdependent EVs which coordinate with each other to achieve their goal. For example, large electric vans can be used for the transportation of goods, between facilities and make en route stops to serve customers or re-stock small electric vans or any other type of smart electric vehicle or station. The integration of various plans to develop intricate delivery systems presents significant research prospects for enhancing overall delivery efficiency in a controlled manner. Most multi-echelon approaches in VRP and EVRP consist of two echelons. Future research can focus on adding more echelons and present multi-objective models with different objectives in each echelon.

4.2.4 Drones and Robots

Drones and robots have created the opportunity for faster and greener transportation, especially when combined with electric vans. As discussed in the previous sections of this study, they can offer great operational agility and savings. Drones in VRP have been researched more, compared to robots; however, only one study exists on the EVRPD and none on the EVRP with robots (EVRPR). This means that there are many opportunities for research in both.

The proposed integration presents a highly valuable area for future research, offering great potential for reducing energy consumption and improving delivery efficiency. Besides the obvious extensions of VRPD variants in order to include EVs, new applications can be developed. Drones can be used to visit automated lockers at known positions, given that lockers have become more popular in recent years. Subsequently, the potential places to visit would remain generally unchanged allowing for a more accurate prediction of energy needs. Drones can also be used for pickup operations, with the objective of minimizing the total energy consumption of the electric van they serve. In heterogeneous fleet scenarios, drones can be used to transfer items between vehicles whenever necessary.

Robots have in general attracted less attention in VRP and have been mainly proposed for use in warehouses and factories. One new scenario to explore with robots in combination with electric vans is their use as mobile lockers for small parcels. Such a combination would lower the total operational time as it would limit the number of times that a driver has to find a parking space and make the delivery. Robots could also be used for trash collection. Instead of having a large EV visit each site in an urban center, robots could be used to eliminate some of the stops, especially in urban city centers with lots of road traffic.

The potential variants to be developed are plenty, with many new insights to be presented, combining elements from different works found in the literature and adding new parameters in an attempt to have a more realistic representation. However, the concurrent use of multiple vehicle types makes the network more complex and introduces new points of failure. In conjunction with the strong coupling between them, the impact of operational failures can be more noticeable compared to the conventional VRPs. To overcome potential setbacks, future research should focus on generating flexible delivery plans with a reasonable level of redundancy.

In addition, while all vehicles operate within the same environment and are affected by the same parameters, the significance level of each parameter to each vehicle type can be different. Therefore, it is important to determine the sensitivity of each type of vehicle to each parameter and evaluate the level of influence it should have. Moreover, some parameters may be interdependent, i.e., a strong headwind will have a toll on the energy consumption of a vehicle traveling at highway speeds, but it would not make a difference in the center of a city.

4.3 New Solution Methods

EVs are both a mode of transportation and a technological product. They are equipped with a variety of sensors and electronic components that generate useful data, such as battery charge levels, charging rates, and energy usage, which can be analyzed to optimize battery life and charging patterns. Additionally, EVs equipped with advanced sensors and driver assistance features generate data on driving behavior and road conditions, which can be used to improve safety and enhance driving efficiency. These features are of high value for logistics operators as that data can be used to assess and improve their operations.

To make such information useful, it is necessary to develop simulation tools that can help recreate different scenarios, evaluate past decisions, and create robust routing plans. The introduction of stochastic energy consumption and the development of data-driven approaches are a great combination for carrying out simulations. By running multiple simulations and analyzing the results, the likelihood of certain events occurring can be estimated, such as a vehicle running out of battery before reaching a charging station. In addition, researchers can simulate different traffic patterns, battery capacities, and charging station locations to see how they affect optimal routing solutions.

A tool that could be used for simulations is artificial intelligence (AI), which has become so popular due to its ability to process and analyze large amounts of data, automate repetitive tasks, improve decision-making, and develop solutions to complex problems. While AI methods have been used in the past to solve VRP problems, there is the opportunity of using AI methods in EVRP simulations. Two methods that could be employed in EVRP are machine learning (ML) algorithms and reinforcement learning (RL) algorithms. ML algorithms can be used to analyze and learn from large amounts of data, making it possible to generate more accurate and efficient EVRP solutions. For example, they can be used to predict traffic patterns and weather conditions, allowing for more accurate route planning. RL algorithms can be used in case data is not available, as RL implementations use the process of trial and error to determine how to make good choices. RL algorithms can be used to continuously improve routing decisions over time by learning from past experiences.

This creates a research opportunity for the development of simulation tools that will help decision-makers determine their EV needs and provide them with adequate knowledge to make informed decisions. Simulations will also give insights in the reliability of EVs for the operations considered.

Furthermore, unlike the conventional VRPs with stochastic environmental variables, such as stochastic travel times and stochastic demand, uncertainty in these novel routing problems with electric vehicles has a pivotal role, as it can disrupt the whole routing operation. For example, uncertainty in payload weight, traffic, or weather conditions can significantly alter the range of operation of an electric vehicle. Combined with uncertainty in the availability of charging stations can be detrimental even to the best-optimized routing plan. Charging stations may be full, not have the available charger, suffer from a temporary failure, or have other issues, as explained in the previous sections. Simulations can help assess the reliability of EVs by exploring different scenarios of charger availability and malfunctions.

Another potential use of such simulations would be their use for the assessment of the routing plans provided by the deterministic heuristic and meta-heuristic algorithms that have been prevalent in VRP research.

4.4 Communication

The novel vehicle types discussed previously are de facto IoT devices, as they incorporate sensors and they have the ability to process data and communicate with each other or other devices. Until the late 2000s and the emergence of the smartphone as the first mobile device connected to the internet, the concept of interconnected autonomous vehicles was far-fetched. Today, autonomous driving vehicles are a technological reality.

These IoT vehicles are able to exchange information instantly, in real time, and thus, have the potential to cooperatively overcome unpredictable events, which otherwise would be detrimental. This adaptive ability of the vehicles, as a swarm, can offer practical benefits which would be unattainable 10 years ago.

Vehicle-to-vehicle communication, referred to as V2V, allows vehicles to exchange information with each other in real time, such as their location, speed, and route. This information can be used to optimize the routing of vehicles in a fleet. For example, if one vehicle in a fleet encounters unexpected traffic or road closures, it can quickly relay this information to the rest of the fleet, allowing them to re-route from an earlier time, instead of reactively following a new route.

Research regarding VRPs should consider leveraging these capabilities in order to not only optimize a static unrealistic version of the problem at hand but also, dynamic and uncertain versions of it. The insights regarding the impact of the adaptive behavior of the vehicle fleets, as well as the coordinating strategies themselves, will be useful from both a theoretical standpoint and in practical applications. Communication between vehicles is an element that is not addressed in existing literature, while it is essential to revolutionizing supply chains.

5 Conclusions

Electric vehicles, such as electric vans, drones, and robots, are very promising, novel means of transportation. This paper presented the technical characteristics along with the advantages they offer and the limitations they impose. Furthermore, the existing literature on VRPs employing electric vehicles, drones, robots, and their possible combinations was reviewed and discussed in terms of realism and applicability, showcasing a research gap between the literature and practical applications.

Sustainability in the supply chain and logistics operations is a critical issue that requires a step-by-step approach to ensure its success. From the perspective of logistics, sustainability in the supply chain and logistics operations refers to the management of environmental, social, and economic impacts throughout the life cycle of goods and materials. This includes the efficient and sustainable transportation of goods, responsible and efficient inventory and materials management, and the promotion of sustainable practices and behaviors among employees, suppliers, and other stakeholders in the supply chain.

The publications presented and the concepts they have introduced have greatly contributed to advancing the VRP field of study. All researchers proposing VRP models utilizing novel means of transportation have provided useful insights on their potential impact. As we move forward, almost 65 years after the VRP was introduced, we should aim to move away from abstracted, static approaches of real-life applications. Research should embrace dynamic environments, stochasticity, and the complexity encountered in practical supply chains, as it is the only way to truly explore the capabilities of those novel means of transportation combined.

In order to make the leap to the next-generation VRPs, based on the discussed publications, the capabilities of the state-of-the-art means of transportation, and the requirements of the modern supply chains for sustainability and autonomy, we proposed the establishment of a common ground for defining and studying novel VRPs and testing solution approaches.

In summary, the proposed elements for the next generations of VRP to consider were the following:

Energy consumption : The topic of energy consumption can provide many opportunities for future research. The use of parameters such as payload and speed should become a part of all energy consumption functions. Stochastic consumption elements should be used to represent energy spent unpredictably. Charging functions, linear and non-linear, should be updated to represent real-world charging functions and explore different strategies for different types of vehicles. In addition, new benchmark instances should be introduced that are closer to reality, thus, providing results that are easier to assess and distinguish from each other, instead of presenting insights based on arbitrary numbers and tests that do not represent reality.

New vehicle types : In the past decade, many new EVs have been presented. Established manufacturers have offered electric variants of their existing EVs, but there are many new manufacturers that have emerged, some of which have created small electric vans which have become very popular. Other types of EVs that have become very popular in the past decade are drones and robots. Future research can focus on maximizing the use of small electric vans and incorporating them into logistics operations that make use of them. Researchers can also focus on the integration of drones and robots in logistics operations with EVs. Heterogeneous fleet compositions should also be studied more thoroughly and EV-specific approaches could be presented.

Dynamic environment : The environment of logistics operations is never static in practice, as it contains unpredictable events and states. The computational capabilities of today make it easy to include dynamic elements and essentially simulate operations in a realistic manner. EVs generate useful data that can be analyzed to optimize their use. This data can be used in simulations that can help operators assess their reliability and foresee potential shortcomings. In addition, simulations can be a useful tool for assessing the feasibility of solutions proposed by deterministic approaches. Future research can focus on the development of simulation tools and transition from deterministic solutions to dynamic ones.

Communication : Vehicles nowadays are IoT devices; therefore, they should communicate, exchange information, and leverage that capability to adapt in real time to changes, such as delays, weather, or other externalities. Contingency plans also have to be developed.

Based on these directions, research on VRP will answer many questions regarding the optimal integration of these novel vehicles, will explore their full potential, and will provide more accurate insights with respect to their true capabilities.

Data Availability

Not applicable.

Dantzig GB, Ramser JH (1959) The truck dispatching problem. Manage Sci 6(1):80–91

Google Scholar  

Kumar SN, Panneerselvam R (2012) A survey on the vehicle routing problem and its variants. Intell Inf Manag 4(3):19355

Helgeson B, Peter J (2020) The role of electricity in decarbonizing european road transport-development and assessment of an integrated multi-sectoral model. Appl Energy 262:114365

Schneider M, Stenger A, Goeke D (2014) The electric vehicle-routing problem with time windows and recharging stations. Transp Sci 48(4):500–520

Xiao Y, Zhang Y, Kaku I, Kang R, Pan X (2021) Electric vehicle routing problem: a systematic review and a new comprehensive model with nonlinear energy recharging and consumption. Renew Sustain Energy Rev 151:111567

Karakostas P, Sifaleras A (2022) Recent trends in sustainable supply-chain optimization. In: Fathi M, Zio E, Pardalos PM (eds) Handbook of smart energy systems. Springer

Patella SM, Grazieschi G, Gatta V, Marcucci E, Carrese S (2020) The adoption of green vehicles in last mile logistics: a systematic review. Sustainability 13(1):6

Hossain M, Kumar L, Islam M, Selvaraj J et al (2022) A comprehensive review on the integration of electric vehicles for sustainable development. J Adv Transp 2022

Goodchild A, Toy J (2018) Delivery by drone: an evaluation of unmanned aerial vehicle technology in reducing CO2 emissions in the delivery service industry. Transp Res Part D: Transp Environ 61:58–67

Pugliese LDP, Guerriero F, Macrina G (2020) Using drones for parcels delivery process. Procedia Manuf 42:488–497

Campbell JF (2022) Will drones revolutionize home delivery? Let’s get real.... Patterns 3(8):100564

Peter O, Pradhan A, Mbohwa C (2023) Industrial internet of things (IIoT): opportunities, challenges, and requirements in manufacturing businesses in emerging economies. Procedia Comput Sci 217:856–865

Psannis KE, Xinogalos S, Sifaleras A (2014) Convergence of internet of things and mobile cloud computing. Syst Sci Control Eng: An Open Access Journal 2(1):476–483

Pourrahmani H, Yavarinasab A, Zahedi R, Gharehghani A, Mohammadi MH, Bastani P et al (2022) The applications of internet of things in the automotive industry: a review of the batteries, fuel cells, and engines. Internet of Things 100579

Qin H, Su X, Ren T, Luo Z (2021) A review on the electric vehicle routing problems: variants and algorithms. Front Eng Manag 8(3):370–389

Quak H, Nesterova N, van Rooijen T (2016) Possibilities and barriers for using electric-powered vehicles in city logistics practice. Transp Res Proc 12:157–169

Juan AA, Mendez CA, Faulin J, De Armas J, Grasman SE (2016) Electric vehicles in logistics and transportation: a survey on emerging environmental, strategic, and operational challenges. Energies 9(2):86

Anosike A, Loomes H, Udokporo CK, Garza-Reyes JA (2021) Exploring the challenges of electric vehicle adoption in final mile parcel delivery. Int J Log Res Appl 1–25

Rojas Viloria D, Solano-Charris EL, Muñoz-Villamizar A, Montoya-Torres JR (2021) Unmanned aerial vehicles/drones in vehicle routing problems: a literature review. Int Trans Oper Res 28(4):1626–1657

Kellermann R, Biehle T, Fischer L (2020) Drones for parcel and passenger transportation: a literature review. Transp Res Interdiscip Perspect 4:100088

Narayanan S, Chaniotakis E, Antoniou C (2020) Shared autonomous vehicle services: a comprehensive review. Transp Res Part C Emerg Technol 111:255–293

Golbabaei F, Yigitcanlar T, Bunker J (2021) The role of shared autonomous vehicle systems in delivering smart urban mobility: a systematic review of the literature. Int J Sustain Transp 15(10):731–748

Fragapane G, De Koster R, Sgarbossa F, Strandhagen JO (2021) Planning and control of autonomous mobile robots for intralogistics: literature review and research agenda. Eur J Oper Res 294(2):405–426

Li H, Chen J, Wang F, Bai M (2021) Ground-vehicle and unmanned-aerial-vehicle routing problems from two-echelon scheme perspective: a review. Eur J Oper Res 294(3):1078–1095

Bahrami S, Nourinejad M, Amirjamshidi G, Roorda MJ (2020) The plugin hybrid electric vehicle routing problem: a power-management strategy model. Transp Res Part C Emerg Technol 111:318–333

Subramanyam A, Cokyasar T, Larson J, Stinson M (2022) Joint routing of conventional and range-extended electric vehicles in a large metropolitan network. Transp Res Part C Emerg Technol 144:103830

Kirsch DA (2000) The electric vehicle and the burden of history. Rutgers University Press. https://books.google.gr/books?id=EqUQAQAAMAAJ

Alizon F, Shooter SB, Simpson TW (2008) Henry ford and the model T: lessons for product platforming and mass customization. In: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, vol 43291. pp 59–66

Thomas V, Maine E (2019) Market entry strategies for electric vehicle start-ups in the automotive industry-lessons from Tesla Motors. J Clean Prod 235:653–663

Hoekstra A (2019) The underestimated potential of battery electric vehicles to reduce emissions. Joule 3(6):1412–1414

Hawkins TR, Singh B, Majeau-Bettez G, Strømman AH (2013) Comparative environmental life cycle assessment of conventional and electric vehicles. J Ind Ecol 17(1):53–64

Verma S, Dwivedi G, Verma P (2022) Life cycle assessment of electric vehicles in comparison to combustion engine vehicles: a review. Mater Today: Proc 49:217–222

Mpoi G, Milioti C, Mitropoulos L (2023) Factors and incentives that affect electric vehicle adoption in Greece. Int J Transp Sci Technol

Mercedes-Benz. Average daily trips. https://www.mercedes-benz.co.uk/vans/en/e-vito-panel-van . Accessed 15 Mar 2022

Kyriakakis NA, Stamadianos T, Marinaki M, Marinakis Y (2022) The electric vehicle routing problem with drones: an energy minimization approach for aerial deliveries. Cleaner Logistics and Supply Chain 100041

Savari GF, Sathik MJ, Raman LA, El-Shahat A, Hasanien HM, Almakhles D, Aleem SHA, Omar AI (2022) Assessment of charging technologies, infrastructure and charging station recommendation schemes of electric vehicles: a review. Ain Shams Eng J 101938

Goetzel N, Hasanuzzaman M (2022) An empirical analysis of electric vehicle cost trends: a case study in Germany. Res Transp Bus Manag 43:100825

Liu K, Wang J, Yamamoto T, Morikawa T (2018) Exploring the interactive effects of ambient temperature and vehicle auxiliary loads on electric vehicle energy consumption. Appl Energy 227:324–331

Ma Y, Ding H, Liu Y, Gao J (2022) Battery thermal management of intelligent-connected electric vehicles at low temperature based on NMPC. Energy 244:122571

Al-Wreikat Y, Serrano C, Sodré JR (2022) Effects of ambient temperature and trip characteristics on the energy consumption of an electric vehicle. Energy 238:122028

Hato Y, Chen CH, Hirota T, Kamiya Y, Daisho Y, Inami S (2015) Degradation predictions of lithium iron phosphate battery. World Electr Veh J 7(1):25–31

Marra F, Yang GY, Træholt C, Larsen E, Rasmussen CN, You S (2012) Demand profile study of battery electric vehicle under different charging options. In: 2012 IEEE Power and Energy Society General Meeting. IEEE, pp 1–7

Kostopoulos ED, Spyropoulos GC, Kaldellis JK (2020) Real-world study for the optimal charging of electric vehicles. Energy Rep 6:418–426

Lin J, Zhou W, Wolfson O (2016) Electric vehicle routing problem. Transp Res Proc 12:508–521

Shao S, Guan W, Bi J (2017) Electric vehicle-routing problem with charging demands and energy consumption. IET Intel Transport Syst 12(3):202–212

Xiao Y, Zuo X, Kaku I, Zhou S, Pan X (2019) Development of energy consumption optimization model for the electric vehicle routing problem with time windows. J Clean Prod 225:647–663

Zhang S, Gajpal Y, Appadoo SS, Abdulkader MMS (2018) Electric vehicle routing problem with recharging stations for minimizing energy consumption. Int J Prod Econ 203:404–413

Basso R, Kulcsár B, Egardt B, Lindroth P, Sanchez-Diaz I (2019) Energy consumption estimation integrated into the electric vehicle routing problem. Transp Res Part D: Transp Environ 69:141–167

Rastani S, Yüksel T, Çatay B (2019) Effects of ambient temperature on the route planning of electric freight vehicles. Transp Res Part D: Transp Environ 74:124–141

Cokyasar T, Subramanyam A, Larson J, Stinson M, Sahin O (2023) Time-constrained capacitated vehicle routing problem in urban e-commerce delivery. Transp Res Rec 2677(2):190–203

Veneri O, Ferraro L, Capasso C, Iannuzzi D (2012) Charging infrastructures for EV: overview of technologies and issues. In: 2012 Electrical Systems for Aircraft, Railway and Ship Propulsion. IEEE, pp 1–6

Jia Q-S, Long T (2020) A review on charging behavior of electric vehicles: data, model, and control. Control Theory Technol 18(3):217–230

Desaulniers G, Errico F, Irnich S, Schneider M (2016) Exact algorithms for electric vehicle-routing problems with time windows. Oper Res 64(6):1388–1405

Ferro G, Paolucci M, Robba M (2018) An optimization model for electrical vehicles routing with time of use energy pricing and partial recharging. IFAC-PapersOnLine 51(9):212–217

Bruglieri M, Mancini S, Pezzella F, Pisacane O, Suraci S (2017) A three-phase matheuristic for the time-effective electric vehicle routing problem with partial recharges. Electron Notes Discrete Math 58:95–102

Ding N, Batta R, Kwon C et al (2015) Conflict-free electric vehicle routing problem with capacitated charging stations and partial recharge. In: Technical Report. Department of Industrial and Systems Engineering, University at Buffalo, US

Çatay B, Keskin M (2017) The impact of quick charging stations on the route planning of electric vehicles. In: 2017 IEEE Symposium on Computers and Communications (ISCC). IEEE, pp 152–157

Zuo X, Xiao Y, You M, Kaku I, Xu Y (2019) A new formulation of the electric vehicle routing problem with time windows considering concave nonlinear charging function. J Clean Prod 236:117687

Froger A, Mendoza JE, Jabali O, Laporte G (2017) A matheuristic for the electric vehicle routing problem with capacitated charging stations

Karakatič S (2021) Optimizing nonlinear charging times of electric vehicle routing with genetic algorithm. Expert Syst Appl 164:114039

Zang Y, Wang M, Qi M (2022) A column generation tailored to electric vehicle routing problem with nonlinear battery depreciation. Comput Oper Res 137:105527

Botsford C, Szczepanek A (2009) Fast charging vs. slow charging: pros and cons for the new age of electric vehicles. In: International Battery Hybrid Fuel Cell Electric Vehicle Symposium. Citeseer, pp 1–9

Li Y, Li K, Xie Y, Liu J, Fu C, Liu B (2020) Optimized charging of lithium-ion battery for electric vehicles: adaptive multistage constant current-constant voltage charging strategy. Renew Energy 146:2688–2699

Keskin M, Çatay B (2018) A matheuristic method for the electric vehicle routing problem with time windows and fast chargers. Comput Oper Res 100:172–188

Froger A, Mendoza JE, Jabali O, Laporte G (2019) Improved formulations and algorithmic components for the electric vehicle routing problem with nonlinear charging functions. Comput Oper Res 104:256–294

Raeesi R, Zografos KG (2020) The electric vehicle routing problem with time windows and synchronised mobile battery swapping. Transp Res B Methodol 140:101–129

Jie W, Yang J, Zhang M, Huang Y (2019) The two-echelon capacitated electric vehicle routing problem with battery swapping stations: formulation and efficient methodology. Eur J Oper Res 272(3):879–904

Raeesi R, Zografos KG (2022) Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping. Eur J Oper Res 301(1):82–109

Ogura K, Kolhe ML (2017) Battery technologies for electric vehicles. In: Electric vehicles: prospects and challenges. Elsevier, pp 139–167

Hjelkrem OA, Arnesen P, Bø TA, Sondell RS (2020) Estimation of tank-to-wheel efficiency functions based on type approval data. Appl Energy 276:115463

Hõimoja H, Rufer A, Dziechciaruk G, Vezzini A (2012) An ultrafast EV charging station demonstrator. In: International Symposium on Power Electronics Power Electronics, Electrical Drives, Automation and Motion. IEEE, pp 1390–1395

WLTP. https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:02017R1151-20190101 &from=EN . Accessed 7 Feb 2023

Jung S, Kim H (2017) Analysis of amazon prime air UAV delivery service. Journal of Knowledge Information Technology and Systems 12(2):253–266

DHL Parcel-copter. https://www.dhl.com/discover/en-global/business/business-ethics/parcelcopter-drone-technology . Accessed 1 Apr 2022

Matternet M2. https://mttr.net/product . Accessed 1 Apr 2022

Zipline Drone. https://en.wikipedia.org/wiki/Zipline_(drone_delivery) . Accessed 1 Apr 2022

Rodrigues TA, Patrikar J, Oliveira NL, Matthews HS, Scherer S, Samaras C (2022) Drone flight data reveal energy and greenhouse gas emissions savings for very small package delivery. Patterns 3(8):100569

Murray CC, Chu AG (2015) The flying sidekick traveling salesman problem: optimization of drone-assisted parcel delivery. Transp Res Part C Emerg Technol 54:86–109

Kitjacharoenchai P, Min B-C, Lee S (2020) Two echelon vehicle routing problem with drones in last mile delivery. Int J Prod Econ 225:107598

Cengiz E, Yilmaz C, Kahraman HT, Suiçmez Ç (2023) Effects of variable UAV speed on optimization of travelling salesman problem with drone (TSP-D). In: Smart applications with advanced machine learning and human-centred problem design. Springer, pp 295–305

Raj R, Murray C (2020) The multiple flying sidekicks traveling salesman problem with variable drone speeds. Transp Res Part C Emerg Technol 120:102813

Wang Z, Sheu J-B (2019) Vehicle routing problem with drones. Transport Res B-Meth 122:350–364

Chauhan D, Unnikrishnan A, Figliozzi M (2019) Maximum coverage capacitated facility location problem with range constrained drones. Transp Res Part C Emerg Technol 99:1–18

Coindreau M-A, Gallay O, Zufferey N (2019) Vehicle routing with transportable resources: using carpooling and walking for on-site services. Eur J Oper Res 279(3):996–1010

Gu Q, Fan T, Pan F, Zhang C (2020) A vehicle-UAV operation scheme for instant delivery. Comput Ind Eng 149:106809

Hu M, Liu W, Lu J, Fu R, Peng K, Ma X, Liu J (2019) On the joint design of routing and scheduling for vehicle-assisted multi-UAV inspection. Futur Gener Comput Syst 94:214–223

Deng P, Amirjamshidi G, Roorda M (2020) A vehicle routing problem with movement synchronization of drones, sidewalk robots, or foot-walkers. Transp Res Proc 46:29–36

Karak A, Abdelghany K (2019) The hybrid vehicle-drone routing problem for pick-up and delivery services. Transp Res Part C Emerg Technol 102:427–449

Kitjacharoenchai P, Ventresca M, Moshref-Javadi M, Lee S, Tanchoco JM, Brunese PA (2019) Multiple traveling salesman problem with drones: mathematical model and heuristic approach. Comput Ind Eng 129:14–30

Rossello NB, Garone E (2020) Carrier-vehicle system for delivery in city environments. IFAC-PapersOnLine 53(2):15253–15258

Li H, Wang H, Chen J, Bai M (2020) Two-echelon vehicle routing problem with time windows and mobile satellites. Transport Res B-Meth 138:179–201

Nguyen MA, Dang GT-H, Hà MH, Pham M-T (2022) The min-cost parallel drone scheduling vehicle routing problem. Eur J Oper Res 299(3):910–930

Zhen L, Li M, Laporte G, Wang W (2019) A vehicle routing problem arising in unmanned aerial monitoring. Comput Oper Res 105:1–11

Shahzaad B, Bouguettaya A, Mistry S, Neiat AG (2021) Resilient composition of drone services for delivery. Futur Gener Comput Syst 115:335–350

Thibbotuwawa A, Bocewicz G, Nielsen P, Zbigniew B (2019) Planning deliveries with UAY routing under weather forecast and energy consumption constraints. IFAC-PapersOnLine 52(13):820–825

Liu Y (2019) An optimization-driven dynamic vehicle routing algorithm for on-demand meal delivery using drones. Comput Oper Res 111:1–20

Macias JE, Angeloudis P, Ochieng W (2020) Optimal hub selection for rapid medical deliveries using unmanned aerial vehicles. Transp Res Part C Emerg Technol 110:56–80

Cheng C, Adulyasak Y, Rousseau L-M (2020) Drone routing with energy function: formulation and exact algorithm. Transport Res B-Meth 139:364–387

Vidal T, Laporte G, Matl P (2020) A concise guide to existing and emerging vehicle routing problem variants. Eur J Oper Res 286(2):401–416

Macrina G, Pugliese LDP, Guerriero F, Laporte G (2020) Drone-aided routing: a literature review. Transp Res Part C Emerg Technol 120:102762

Cheikhrouhou O, Khoufi I (2021) A comprehensive survey on the multiple traveling salesman problem: applications, approaches and taxonomy. Comput Sci Rev 40:100369

Moshref-Javadi M, Winkenbach M (2021) Applications and research avenues for drone-based models in logistics: a classification and review. Expert Syst Appl 177:114854

Chung SH, Sah B, Lee J (2020) Optimization for drone and drone-truck combined operations: a review of the state of the art and future directions. Comput Oper Res 123:105004

Amazon Scout. https://www.dimensions.com/element/amazon-scout . Accessed 1 Apr 2022

Starship Robot. https://www.post.ch/-/media/post/ueber-uns/medienmitteilungen/ 2017/factsheet-lieferroboter.pdf?la=en . Accessed 1 Apr 2022

Teleretail Delivery Robot. https://www.dimensions.com/element/teleretail-delivery-robot . Accessed 1 Apr 2022

Deliro Delivery Robot. https://www.dimensions.com/element/deliro-delivery-robot . Accessed 1 Apr 2022

Kiwibot. https://www.dimensions.com/element/kiwibot . Accessed 1 Apr 2022

Serve Robotics. https://www.dimensions.com/element/serve-serve-robotics . Accessed 1 Apr 2022

Fed-Ex Roxo. https://www.dimensions.com/element/fedex-roxo . Accessed 1 Apr 2022

Nuro R2. https://www.dimensions.com/element/nuro-r2 . Accessed 1 Apr 2022

Boysen N, Schwerdfeger S, Weidinger F (2018) Scheduling last-mile deliveries with truck-based autonomous robots. Eur J Oper Res 271(3):1085–1099

Alfandari L, Ljubić I, da Silva MDM (2022) A tailored benders decomposition approach for last-mile delivery with autonomous robots. Eur J Oper Res 299(2):510–525

Ostermeier M, Heimfarth A, Hübner A (2022) Cost-optimal truck-and-robot routing for last-mile delivery. Networks 79(3):364–389

Heimfarth A, Ostermeier M, Hübner A (2022) A mixed truck and robot delivery approach for the daily supply of customers. Eur J Oper Res 303(1):401–421

Chen C, Demir E, Huang Y (2021) An adaptive large neighborhood search heuristic for the vehicle routing problem with time windows and delivery robots. Eur J Oper Res 294(3):1164–1180

Chen C, Demir E, Huang Y, Qiu R (2021) The adoption of self-driving delivery robots in last mile logistics. Transp Res E: Logist Transp Rev 146:102214

Jennings D, Figliozzi M (2019) Study of sidewalk autonomous delivery robots and their potential impacts on freight efficiency and travel. Transp Res Rec 2673(6):317–326

Figliozzi M, Jennings D (2020) Autonomous delivery robots and their potential impacts on urban freight energy consumption and emissions. Transp Res Proc 46:21–28

Simoni MD, Kutanoglu E, Claudel CG (2020) Optimization and analysis of a robot-assisted last mile delivery system. Transp Res E: Logist Transp Rev 142:102049

Yu S, Puchinger J, Sun S (2022) Van-based robot hybrid pickup and delivery routing problem. Eur J Oper Res 298(3):894–914

Bakach I, Campbell AM, Ehmke JF (2021) A two-tier urban delivery network with robot-based deliveries. Networks 78(4):461–483

Poeting M, Schaudt S, Clausen U (2019) A comprehensive case study in last-mile delivery concepts for parcel robots. In: 2019 Winter Simulation Conference (WSC). IEEE, pp 1779–1788

Poeting M, Schaudt S, Clausen U (2019) Simulation of an optimized last-mile parcel delivery network involving delivery robots. In: Interdisciplinary Conference on Production, Logistics and Traffic. Springer, pp 1–19

Download references

Author information

Authors and affiliations.

School of Production Engineering and Management, Technical University of Crete, University Campus, Akrotiri, 73100, Greece

Themistoklis Stamadianos, Nikolaos A. Kyriakakis, Magdalene Marinaki & Yannis Marinakis

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Yannis Marinakis .

Ethics declarations

Conflict of interest.

The authors declare no competing interests.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Stamadianos, T., Kyriakakis, N.A., Marinaki, M. et al. Routing Problems with Electric and Autonomous Vehicles: Review and Potential for Future Research. Oper. Res. Forum 4 , 46 (2023). https://doi.org/10.1007/s43069-023-00228-1

Download citation

Received : 19 May 2022

Accepted : 15 May 2023

Published : 31 May 2023

DOI : https://doi.org/10.1007/s43069-023-00228-1

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Electric vehicles
• Vehicle routing problem
• Find a journal
• Publish with us
• Track your research

Create an account

Create a free IEA account to download our reports or subcribe to a paid service.

• Onshore wind
• Ocean power
• Offshore wind
• CCUS in power
• Nuclear power
• Fuel supply
• Data centres & networks
• Building envelopes
• Appliances & equipment
• Pulp & paper
• CCUS in industry & transformation
• Iron & steel
• Fuel economy of cars & vans

Electric vehicles

Transport biofuels.

• Trucks & buses

International shipping

Cite report.

IEA (2019), Innovation Gaps , IEA, Paris https://www.iea.org/reports/innovation-gaps, Licence: CC BY 4.0

Share this report

• Share on Twitter Twitter
• Share on Facebook Facebook
• Share on LinkedIn LinkedIn
• Share on Email Email
• Share on Print Print

Innovation on efficiency technologies and low-carbon vehicles and fuels is particularly important in harder-to-abate modes

Transitioning towards sustainable transport will require improving vehicle efficiency and adopting low carbon vehicle and fuel technologies. Innovation can accelerate the transition by cutting costs, promoting technology learning, and improving performance of both conventional and zero-emission vehicles (electric or fuel cell electric).

Innovation on efficiency technologies and low-carbon vehicles and fuels is particularly important in harder-to-abate modes like heavy-duty vehicles, maritime and aviation, where technologies that are currently commercially available alone cannot deliver the emission reductions seen in the SDS.

Innovation can also play an important role in improving systems-level efficiency. For instance, innovation in digital technologies -- from communications to deep learning algorithms -- can help match and optimise transport supply and demand.

Fuel economy of cars & vans

The car industry is one of the highest spenders on research and development.

The car industry is one of the highest spenders on research and development, representing nearly 25% of global R&D spending in 2018 (Auto Alliance, 2018).

Numerous technologies can lead to fuel economy improvements, including:

• energy efficient tires
• improved aerodynamics
• fuel efficient combustion technologies and engine downsizing
• powertrain electrification

Reducing vehicle weight is a key means to improve fuel efficiency. Lightweighting techniques such as using high-strength steel and aluminium in the chassis can reduce the mass of the vehicle while cutting both fuel consumption and total life-cycle CO 2  emissions (Serrenho, 2017).

So far, however, most of the fuel economy benefits of lightweighting have been offset by the increased weight of upscale features, safety enhancements and increased vehicle size in many markets.

Gap 1: Advanced internal combustion engine technologies

Why is this gap important?

Despite the increasing market share of EVs, IEA scenarios show that a large share of the LDV fleet will be powered by internal combustion engines (ICEs) in conventional, hybrid and plug-in hybrid configurations until at least mid-century. Reducing ICE CO 2  emissions is thus a key part of a balanced strategy for limiting atmospheric CO 2  levels. Improving ICEs is also a cost-effective CO 2  mitigation strategy.

ICEs operating on electrofuels generated when excess renewable electricity is available may even promote more rapid decarbonisation of the electricity supply while providing near-zero carbon emissions. Additional CO 2  emissions reductions could also be gained through the use of bio-derived or other low-carbon fuels along with ICE design optimisation to take full advantage of their properties.

Reducing local pollutant emissions of particulate matter, unburned hydrocarbons and nitrogen oxides from ICEs remains an important challenge. The move to vehicle hybridisation with start-stop systems can also result in higher pollutant emissions if exhaust after-treatment devices are not operating effectively (SAE, 2018).

Technology solutions

A number of viable technologies are ready or are being introduced into the market, though there is potential for improvement. Many of these TRL 8‑10 technologies are currently being introduced in luxury vehicles.

• Low-friction cylinder wall finishes, bearings and rings, and electrified accessories such as water pumps, all reduce parasitic losses.
• Cooled exhaust gas recirculation (EGR); improved air handling and turbocharging.
• Variable valve actuation technologies (VVA), including both variable timing (VVT) and lift (VVL), particularly important for light-load urban fuel efficiency and emissions.
• Hybrid technologies range from fully hybrid powertrain topologies (e.g. the Toyota Prius) through more modest partial hybridisation (e.g. the 48V Mercedes S-class) to the now-ubiquitous start-stop systems.
• Advanced diesel engine combustion designs, e.g. new bowl geometry reduce emissions and improve efficiency (e.g. Volvo).
• Variable compression ratio (VCR) engines (e.g. Nissan) operate efficiently at low to intermediate loads while preserving high power density and good peak-load performance.
• Alternative engine architectures that reduce heat losses or minimise combustion duration (high ‘tumble’ air flows and larger engine stroke-to-bore ratios).

Significant advances in our understanding are also needed. These measures are typically characterised as TRL 3‑7:

• Measures to reduce engine knock and low-speed pre-ignition, which limit compression ratio and powertrain system operations in mainstream downsized, boosted spark-ignition (SI) engine technologies.
• Approaches to maintain rapid combustion and high-efficiency over the full operating range when VVA is employed.
• Improved aftertreatment catalyst formulations and strategies to reduce catalyst warm-up time.
• Strategies to reduce particulate mass and number in direct-injection engines (both diesel and gasoline), without adversely impacting efficiency.
• Advanced ignition concepts (e.g. plasma-based igniters or turbulent jet igniters) to improve knock resistance and enable more efficient, lower-emission operations for both conventional SI and lean combustion technologies.
• Reduced heat losses through combustion system design or deployment of thermal barrier coatings (also enhances after-treatment performance and waste heat recovery).
• Advanced strategies for reducing pumping work or knock, such as water injection, on-board fuel reformation and partial fuel reformation strategies (e.g. SwRI-dedicated EGR).
• Fuel-lean combustion technologies are a key opportunity for efficiency, but require:
• Cost-effective HC/NOx aftertreatment adapted to the low exhaust gas temperatures of lean, high-compression/expansion-ratio engines (includes diesels).
• Reliable ignition for very lean mixtures and improved low-load stability.
• Effective control strategies for highly efficient kinetically controlled combustion.
• Control of both NOx and particulate emissions in stratified combustion systems.
• Alternative engine architectures such as split-cycle (e.g. Volvo or Ricardo), or opposed-piston designs (e.g. Achates).
• Dual fuel concepts that could provide very high efficiency, low emissions and improved control, but are in the very early stages of development.

What are the leading initiatives?

Numerous programmes within government research laboratories, universities, engine design consultancies and car-part suppliers are working to close the science and technology gaps identified above. The following are the key institutes or programmes funded either by governments or large industrial consortiums (for-profit organisations have been omitted):

European Union

• FVV  (Forschungsvereinigung Verbrennungskraftmaschinen) is a large consortium of companies, universities, research centres and funding organisations that funds ICE research in numerous areas that impact both efficiency and emissions.
• IFP Energies nouvelles  (Institut français du pétrole) is a public research organisation that researches a broad range of transportation technologies.
• The government-funded  Strategic Innovation Program  (SIP) ended successfully in May 2018 after demonstrating a peak SI engine thermal efficiency of 51.5% (including waste heat recovery).
• The Association of Internal Combustion Engines  (AICE) is an industry consortium of 8 OEMs and more than 80 suppliers that funds JPN 200 million (USD 2 million) worth of university research on LDVs.
• The New A.C.E. Institute, funded by a consortium of approximately ten OEMs and suppliers, focuses on advance diesel research with a budget of roughly JPN 200 million (USD 2 million).
• Japan Automobile Research Institute  (JARI) researches a variety of transportation technologies, including ICEs, EVs, and FCVs.

United States

• The US Department of Energy funds engine research at the US national laboratories as well as at universities and in industry through a competitive proposal process, with an approximate budget of USD 64 million per year.
• The Southwest Research Institute performs in-house contractual research and operates two industry-funded consortiums focused on clean and efficient gasoline engines ( HEDGE ) and diesel combustion ( CHEDE ).

Recommended actions

• Industrial producers should in the next 5 years ensure continued R&D funding; and in the next 5 to 10 years formulate policies that: incentivise consumer acceptance of higher initial product costs in return for lower total ownership costs; are technology-neutral; provide enough lead time for robust product development that will be accepted by consumers and give companies profit-making opportunities; and ensure transportation access to all sectors of society by promoting cost-effective solutions.
• Industry/companies should in the next 5 to 10 years onvest in R&D and rollout-proven technologies in vehicle fleet

Gap 2: Lightweighting of light duty vehicles (LDVs)

Although the average weight of new LDVs remained relatively stable globally during 2015‑17, in more than two-thirds of countries average LDV weight actually increased – with increases in three-quarters of countries in 2016‑17 alone. This is the result of three counterbalancing trends: first, growth in the market share of large LDVs (SUVs and pick-up trucks) raised vehicle weight.

At the same time, however, an increasing volume (and share) of vehicles were being sold in emerging economies. These vehicles tend to be smaller and lighter than new vehicles sold in advanced economies, which tempered the effect of higher large-LDV sales.

Finally, lightweight materials such as advanced high-strength steel, aluminium, thermoplastics and even carbon fibre composites are used more widely in new LDVs sold in all markets because they have the potential to improve safety, performance and fuel economy while making the vehicle lighter.

Reducing vehicle weight is a key means to improve fuel efficiency. Lightweighting techniques such as using high-strength steel and aluminium in the chassis can reduce the mass of the vehicle while cutting both fuel consumption and total life-cycle CO2 emissions (Serrenho, 2017). So far, however, most of the fuel economy benefits of lightweighting have been offset by the increased weight of upscale features, safety enhancements and increased vehicle size in many markets.

In recent decades, advanced (high-strength) steel architectures has successfully incorporated lighter, stronger and more durable composites into car bodies, chassis and closures. Many of these elements are already fully commercial (TRL 10‑11), but more advanced designs at lower technology readiness are also being developed. Aluminium components have also been used for car bodies and other parts. As with steel, aluminium producers are constantly developing stronger alloys, and sheet improvements are especially pronounced. Depending on fuel economy policies and the competitiveness of raw material prices, it is likely that aluminium will be increasing used to make hoods, doors, trucks, roofs and fenders in the upcoming decade.

Thermoplastics and composites are more recent additions to the structural and weight- and stress-bearing components of automobiles. Their application will depend on whether material and manufacturing process innovations allow them to be adopted cost-effectively in large-scale car manufacturing, whether their production can be made less energy-intensive, and whether recycling processes can be designed.

• Many national governments are introducing fuel economy standards into their regulatory frameworks. Most fuel economy standards use a target curve to accommodate the origins of various car makers, and the main metrics for target curves are either weight-based or footprint-based. Governments that opt for a weight-based fuel economy standard reduce the necessity for car makers to reduce vehicle weight, however, as a higher average weight allows higher average fuel consumption to meet the target.
• Car manufacturers and part suppliers are developing materials and designing cars that weigh less for a similar size.
• Materials scientists and other researchers are developing innovative materials and production processes, for instance novel ways to mass-produce and recycle carbon fibre-reinforced polymer composite materials. Such materials could make cars and trucks safer and more efficient, and they also show promise for other transport modes such as aviation.
• National governments should in the near-term adopt footprint-based fuel economy standards to incentivise weight-reduction technology developments and meet corporate average fuel economy targets that would partially offset impaired fuel economy improvements in many countries. Another solution could be to implement a direct weight-reduction target; consider life-cycle energy, emissions and sustainability impacts when designing regulations; and support basic materials science research in academic and government laboratories, and design policies to promote innovation in industry.
• Car manufacturers and part suppliers should in the next 5-10 years develop materials and design cars that weigh less for a similar size. 
• Researchers and industry scientists should in the next 5 years and continuously design materials and components that are easily disassembled and recycled.

Innovation in EVs fundamentally needs to focus on continued improvements of the battery technology itself

Innovation in EVs fundamentally needs to focus on continued improvements of the battery technology itself, including advancing alternative chemistries, to reach the cost, density and efficiency needed to reach the levels of deployment in the SDS.

These innovation efforts can also support more sustainable manufacturing and value chains for the large volumes of batteries produced under the SDS.

As the share of EVs increases, their impact on electricity networks, particularly on distribution grids, will become larger. If EV charging is deployed and managed smartly however, EVs can become a flexibility resource able to aid in their own integration and that of higher shares of variable renewables or other distributed energy resources into the grid.

Gap 1. Advancing technologies and reducing battery costs

In the SDS, annual EV battery deployment is 30 times higher by 2030. Reaching this level of deployment will require continued cost reductions, and battery efficiency and density improvements beyond what can be achieved with current technologies.

Electric cars currently cost more to purchase than similar-sized conventional cars, and even from a total cost of ownership perspective (including operational costs such as fuel), the economic advantages of electrification are limited to a relatively narrow range of cases. The cost challenges related to EVs are primarily linked to the battery, one of the major cost components. Technological advances allowing for more compact batteries with longer ranges, extra durability (the capacity to withstand a large number of charge/discharge cycles without performance being affected) and the capacity to charge at very high power (fast/ultra-fast charging, from 100 kW to 1 MW), will also influence level of EV adoption.

EV batteries currently focus on Li-ion technologies with a range of chemistries (e.g. nickel cobalt aluminium oxide [NCA], nickel manganese cobalt [NMC] and lithium iron phosphate [LFP], the last being the most used today).

With growing volumes of EVs on the market, battery costs and technology evolutions are happening rapidly, and two trends are currently being observed:

• Lithium-ion battery costs per kWh are decreasing every year thanks to economies of scale in manufacturing and larger battery packs per vehicle.
• Increasingly, EV manufacturers offer various battery sizes for the same model to meet consumer needs as much as possible and thus optimise vehicle price for the consumer.

Indications from recent assessments of battery technologies suggest that Li-ion is expected to remain the technology of choice for the next decade. The main developments in cell technology that are likely to be deployed in the next few years include:

• For the cathode, the reduction of cobalt content in existing cathode chemistries, aiming to reduce cost and increase energy density, i.e. from today’s NMC 111 to NMC 622 by 2020, or from the 80% nickel and 15% cobalt of current NCA batteries to higher shares of nickel (Meeus, 2018; Nitta et al. 2015; Chung and Lee, 2017).
• For the anode, further improvement to the graphite structure, enabling faster charging rates (Meeus, 2018).
• For the electrolyte, the development of gel-like electrolyte material (Meeus, 2018).

The next generation of Li-ion batteries entering the mass production market around 2025 is expected to have low cobalt content, high energy density and NMC 811 cathodes. Silicon can be added in small quantities to the graphite anode to increase energy density by up to 50% (Meeus, 2018), while electrolyte salts able to withstand higher voltages will also contribute to better performance.

Cathode chemistries in Li-ion NMC batteries are already moving rapidly towards higher shares of richer nickel chemistries (422 and 532, and to a lower extent up to 622 and 811). The intention is to reduce the quantity of cobalt in NMC batteries, recently associated with unstable prices.

In the 2025-30 period, technologies that promise significantly higher energy densities are likely to begin entering the market and will push the limits of Li-ion batteries (advanced Li-ion). For example, lithium metal cathodes are a promising technology for Li-ion batteries with improved performance without relying on cobalt, and anodes made of silicon composite might also enter the design.

In the longer term, the research community is particularly investigating solid-state batteries and post-Li‑ion technologies, such as lithium-sulphur and lithium-air. Solid-state batteries use solid electrolytes to accommodate faster charging and have a higher energy density and better durability. However, the fact that this technology operates better in high temperatures (solid electrolytes have lower conductivity at low temperatures) is a challenge for their suitability in automotive applications, especially in temperate to cold climates, so materials and innovations capable of overcoming this are at the centre of research. Lithium-sulphur and especially lithium-air batteries are options for which the theoretical energy density would be maximised, but they are quite a few years away from reaching mass market deployment.

While lithium-ion batteries with NMC cathodes are in phase IV of technology readiness development, solid-state batteries are aimed to enter phase III by 2028 and phase IV by 2030. Post‑Li-ion technologies are currently considered to be at TRL 3, and the EC's goal is to reach TRL 7 by 2030 and TRL 9 by 2035, according to their TRL scale (EC, 2018).

• Half of the battery cells production for electric light-duty vehicles is concentrated in China, with the rest divided among the United States, Korea and Japan. Large private sector stakeholders (such as BYD and CATL, which account for more than half of the Chinese market, and LG Chem, Panasonic, Samsung SDI and SK Innovation) are at the core of automotive battery development, both in terms of scale and technology improvement.
• Other stakeholders involved in advancing costs reductions and technology performance of automotive batteries include government institutions and research laboratories. For example, the European Battery Alliance proposed an implementation plan to create a common understanding of state-of-the-art battery technology development, define the main innovation targets for upcoming years (relative to energy density, fast-charging capability, battery durability, pack cost and manufacturing volumes), and define a pathway for achieving specific TRLs in the future (EC, 2018).
• Large investments in solid-state battery research are also being made in Japan, where an alliance of Japanese manufacturers is joining forces (with public support from Japan’s New Energy and Industrial Technology Development Organization) to develop solid-state batteries (Nikkei, 2018). Recently, Toyota and Panasonic also created a joint venture with the aim of developing solid-state batteries in the first half of the 2020s, and they intend to do so for various automakers (Toyota, 2019).
• Environment, energy and resource ministries should in the next 5 years facilitate exploratory research, developing combinatorial materials for radically novel systems, including metal-air, solid-state, magnesium-based, fluoride or chloride-ion, etc; develop awareness in R&D strategies about using raw materials that will not be considered scarce or environmentally problematic; develop and expand strategies for research and demonstration on the use of second-hand batteries provided by the transport sector for stationary storage, which could alleviate some of the pressures of reaching lower cost targets for the power sector; and governments should strengthen industrial leadership through accelerated research and innovation support, particularly for advanced lithium-ion and solid-state technologies.
• Multilateral Development agencies should in the next 5 to 10 years promote funding and collaborative activities for innovative low-carbon technologies in the battery storage industry.
• NGOs and think tanks should in the next 5 to 10 years raise awareness of environmental and social impacts of the battery supply chain; and raise awareness on the relevance of electric mobility and battery storage for the clean energy transition.
• Industry should in the next 5 to 10 years co‑operate with the public sector to better understand which policies should be prioritised for the development of battery industry value chains, maximising the benefits available from cases in which industries already have a competitive advantage and helping public authorities understand which conditions would facilitate investments in other areas of the battery value chain; join forces and co‑operate across the battery value chain to reduce investment risks and facilitate the emergence of mutual benefits, e.g. due to scale and asset sharing; increase international collaboration to identify and raise awareness of the key challenges in taking key early-stage battery technologies to the market, focusing particularly on the long-term view beyond current Li-ion technology; and reduce balance-of-system and integration costs for the new generation of low-cost batteries.

Gap 2. Allowing EVs to become a flexibility resource for the grid

High EV uptake with unmanaged charging can pose a challenge for the power system if charging coincides with the high-demand periods of the main power system, resulting in greater peak demand and requiring additional peak generation capacity. Increasing EV uptake can also overload distribution networks and necessitate local power grid upgrades such as transformer replacements and cable reinforcement.

Conversely, if adequately managed, EVs can also provide demand-side response (DSR) solutions across a wide range of timescales. Unlocking DSR opportunities from the participation of EVs would help integrate a higher share of variable renewables such as wind and solar power as well as other distributed energy resources. This is a major opportunity given the challenges of electricity system operators to conciliate supply and demand while integrating greater shares of variable renewable energy and other distributed energy resources.

Reaping this potential requires digital platforms and mechanisms to unlock the DSR capability of EVs. In most countries, however, the necessary elements have not been developed enough to optimally accommodate increased EV uptake. This includes smart-meter deployment and other advanced metering infrastructure; electricity markets operating at various time-scales (from the second to the year); regulations that allow distributed generators to participate in the market and aggregate their flexibility capacity; and the physical ability to control vehicle charging and/or allow for bidirectional electricity flows.

Fundamentally, a charging system is needed that allows control over power delivery, potentially able to change the charging current. Open-charge protocols can overcome the lack of charging current control in today's chargers by acting between the operator and the charging point (TRL 8). Progress in advanced metering infrastructure is uneven across countries, even if strong growth is expected in key regions such as India and Southeast Asia by 2025. 

Crucially, interoperability is needed between the grid and charging infrastructure, e-mobility control and management systems, and vehicle and consumer interfaces. Arrangements for smart charging may be complex and involve third parties, distribution system operators (DSOs), utilities, car manufacturers and other stakeholders: ICT standards and protocols need to facilitate communication between all parties and the DSO responsible for overseeing and co‑ordinating grid operations. Most of these protocols have not been tested at scale.

Vehicle-to-grid systems cost three to five times more than standard smart charging (IRENA, 2019). There is currently no standard technology to monitor the state of a vehicle’s charge, and V2G communication protocols for intelligent devices and electrical substations are yet to be deployed and standardised at scale.

Forms of smart charging are multiple but generally require that dynamic electricity pricing be directly available to the consumer (so that the consumer can choose when to charge the vehicle). More importantly, aggregators (the interface between the individual EV consumer and electricity markets or grid operators) need to be allowed to provide a range of services. Aggregators are essential to a system with distributed flexibility sources. If they are empowered to pool together EVs (and/or other electrical devices) at a large enough scale, they can trigger effective demand-side responses by aggregating the monetary benefits available from differentiated electricity prices (e.g. across times of the day) from participating in different power markets.

Finally, numerous countries lack competitive arrangements in wholesale, balancing and capacity markets, which are essential to maximise the benefits of EV flexibility services. If EVs do not have access to price-based, dynamic control of their charging time (or to more complex forms of smart charging such as vehicle-to-grid), the only visible EV impacts on the grid may be overloads of local networks (or the entire system at peak times).

Countries with high EV penetrations, such as those in Northern Europe, have already gained experience in pooling together and co‑ordinating the charging of many EVs, with a visible positive impact on the power grid. The figure below shows how the charging capacity of 1 000 EV charging sessions in the Netherlands are pooled by the aggregator Jedlix and respond to price signals, resulting in a significant change in the power draw of EVs to off-peak demand hours – in comparison with 1 000 charging sessions not subject to the price signals.

Additionally, China, the United States, Japan and a number of European countries lead in smart-meter deployment, with China having deployed close to 500 million by 2017 and several countries poised to reach full rollouts over the next several years (IEA, 2018b).

The Parker project in Denmark is developing smart charging services to a fleet of electric vehicles to provide grid-balancing services.

• Think tanks/governments/energy regulators should in the next 5 years create new market participants (non-existent in a traditional electricity market configuration) such as aggregators and virtual power plants, capable of pooling flexibility resources from distributed electrical devices; empower participants that can provide early aggregation capacity: as ‘natural’ aggregators, managers of EV fleets are well placed to explore the flexibility solutions their EV fleet could provide to the grid; open current electricity markets to a larger panel of participants (such as aggregators and, to some extent, individuals) and adapt regulations when needed to facilitate market access; where absent, create electricity markets to provide system services, capacity or reserves, enabling EVs to bid on demand-response services; governments, regulators and utilities should revise grid codes to reduce the impacts of high, localised EV loads on power quality. Empower DSOs to better understand and design standards
• Utilities, grid owners and operators should in the next 5 to 10 years expand investment in grid-wide monitoring and big data analytics when necessary through changes in regulatory incentives.
• Standards bodies, equipment manufacturers and regulators should in the next 5 to 10 years develop software and interoperability protocols allowing communication among EVs, aggregators, grid markets and operators at all levels.
• Energy and Resource Ministries should in the next 5 to 10 years study the cost impact of technical elements for EVs and the related charging infrastructure needed for controlled, bi-directional charging, and develop technologies able to minimise this impact (costs will also fall as technology deployment accelerates).
• Technical research organisations (industry, academia, research institutes) should in the next 5 to 10 years study the impact of controlled and bi-directional charging on battery durability, and develop technologies to minimise this impact.

Advanced biofuels need to command a more significant share of transport biofuel consumption by 2030 in the Sustainable Development Scenario

Advanced biofuels need to command a more significant share of transport biofuel consumption by 2030 in the SDS. However, currently only biodiesel and HVO production from fat, waste oil and grease feedstocks is commercialised, and there are limits on the availability of these feedstocks.

Therefore, scaling up advanced biofuel production volumes significantly needs innovation so other less mature advanced biofuel technologies reach commercial production. Cellulosic ethanol and biomass-to-liquid (BtL) synthetic fuels are important in this respect. This is because they can be produced from feedstocks with higher availability and potentially lower cost, such as municipal solid waste, forestry and agricultural residues. 

Gap 1. Commercialisation of cellulosic ethanol

Cellulosic ethanol offers significant CO 2  emissions reductions compared with fossil-based transport fuels for internal combustion engine (ICE) passenger vehicles, as well as for trucks and buses when used as ED95 (95% fuel ethanol with lubricants and additives). Although regular vehicles can accommodate ethanol at low blend rates, CO 2  emissions reductions are maximised when it is used at high blend shares or unblended in flexible-fuel vehicles. Higher cellulosic ethanol production would also provide the additional benefit of curtailing agricultural residue-burning in fields, which deteriorates air quality. 

Cellulosic ethanol is one of the advanced biofuels closest to commercialisation, currently at TRL 8 level. Commercial-scale plants in Brazil, Europe and the United States came online during 2013‑16, but their performance has so far been mixed.

Some of these plants are offline due to non-technical issues, while others demonstrate progress in scaling up output but production remains below rated capacity. These plants are in an extended commissioning phase because of the intensive learning curve required to raise yields and utilisation rates through core-process optimisation, design improvements and further modifications to improve process reliability. Important breakthroughs in pre-treatment have been made by several of these plants in the last two years, and improved performance will reduce investment and operational costs for the next generation of projects.

The United States, Europe, Brazil and India lead cellulosic ethanol development owing to a combination of complementary industry and agricultural sectors as well as policy support.

For example, the US Renewable Fuel Standard has a dedicated requirement for cellulosic biofuels, while India has pledged to develop 12 commercial-scale cellulosic ethanol plants.

• Government energy and transport departments should in the next 5 years introduce or sustain policy measures to guarantee long-term demand (e.g. advanced biofuel mandates) and encourage existing cellulosic ethanol plants to persevere with activity to raise yields and utilisation rates; and provide policy support to encourage investment, e.g. financial de-risking measures. Key countries/regions: As ethanol can be transported globally demand from any country would support commercialisation efforts. However, at current costs advanced economies are likely to have a key role.
• Industry should in the next 5 years continue to improve yields and utilisation rates to meet investment criteria for replication plants; and exploit synergies between conventional and cellulosic ethanol production to form integrated facilities that cost less and build on existing feedstock availability, infrastructure and expertise. Key countries/regions:  Europe, Brazil and the United States, as they already have commercial-scale cellulosic ethanol facilities.
• Academia should in the next 5 years undertake benchmarking studies on cellulosic ethanol CO2 emissions reductions, and analyse potential production volumes in different regions based on current and future feedstock availability. Key countries/regions:  Globally, although institutions in countries with significant agricultural residue availability, e.g. China and India, are especially relevant.
• NGOs and think tanks should in the next 5 years provide clear and balanced information on cellulosic ethanol and other advanced biofuels, highlighting the benefits they can offer and sustainability concerns they mitigate.

Gap 2. Development of biomass-to-liquids fuel production from thermochemical processes

Biomass-to-Liquids (BtL) synthetic fuels produced from thermochemical processes, such as gasification and pyrolysis, offer the potential to convert low value biomass and waste feedstocks (including municipal solid waste) to low carbon transport fuels. The high availability of these feedstocks means that fully commercialised thermochemical technologies could open the door to significant volumes of advanced biofuels for the transport sector, providing diesel substitutes in sectors that are hard to electrify.

There are various BtL technology pathways to produce transport biofuels. These are generally at a technology readiness level between 5-7 e.g. development and demonstration. However, one BtL technology has reached TRL 8 first-of-a-kind commercial scale.

BtL fuel production remains low. Some plants have failed to successfully operate once built and multiple announced projects have not been developed. Several challenges slow technology development, such as:

• Tar formation causing operational problems with downstream equipment.
• Slagging and fouling with certain feedstocks limiting plant availability.
• Difficulties with handling, storage and transportation of certain biomass and waste feedstocks. 

There is also the need to lower BtL fuel production costs.

One plant is producing methanol and ethanol from municipal solid waste in Canada, with replication projects in development. In the United States two commercial scale projects based on gasification and FT to produce aviation biofuels are in the later stages of development. Sweden and Finland are also at the forefront of project development in the area of BtL fuels.

Countries with advanced biofuel policy frameworks e.g. several European Union member states and the United States are likely to lead future BtL development. These may open the door for future technology leapfrogging in other countries with significant feedstock availability should costs reduce. 

• Industrial producers should in the next 10 years demonstrate long term operation of demonstration and first-commercial BtL facilities. This will facilitate commercialisation and an improved indication of BtL fuel production costs; optimised methods to convert or remove tars including identification of suitable scrubbing liquids and cracking measures Key countries/regions:  Regions with active BtL project development e.g. Europe, North America; and demonstrate the co-processing of biomass feedstocks and the upgrading of fuel precursors in refineries.
• Academia should in the next 10 years research on the optimisation of BtL processes for different biomass and waste feedstocks. Key countries/regions:  Focusing on regions with significant feedstock availability. Continued R&D on syngas/pyrolysis oil cleaning and upgrading to transport fuels.
• Standardisation bodies, with vehicle original equipment manufacturers (OEMs) should in the next 5 years establish recognised standards for BtL fuel use and production. Key countries/regions:  Focused on key markets e.g. countries and regions with supportive policies for advanced biofuels.

Trucks & buses

There is a need for alternative infrastructure and operational models for long-haul trucking.

With the exception of the long-range Tesla semi variant and the prototype Nikola trucks, the range of zero-emission trucks is limited to below 600 kilometres. Together with the time required to recharge depleted batteries (or the high amperage, voltage, and power draw requirements of very fast charging), this points to the need for alternative infrastructure and operational models for long-haul trucking.

To date, three competitors seem most promising: dynamic charging on Electric Road System (ERS) corridors; continuing improvements in the performance, capacity, and costs of advanced lithium batteries; and hydrogen.

Gap 1. Cost-competitive hydrogen fuel cell systems for FCEVs

There are two main types of zero-emissions vehicles: BEVs and FCEVs. Because of the long charging time and short range of EVs, FCEVs hold promise as a complementary technology, but they remain costly and their availability is limited. Transport modes such as trucks, buses, maritime and locomotive applications, may particularly benefit from fuel cell rather than pure electric, battery-based drivetrains. Several steps can be taken to reach cost targets: reduce precious metal use by downsizing the fuel cell stack; boost production of fuel cells and all ancillary components to obtain economy-of-scale cost reductions; and deploy targeted refuelling infrastructure tailored to specific modes and applications.

In 2018, around 4 000 FCEVs were sold around the world (TRL-8). Toyota Motor is currently the world's leading FCEV producer and plans to increase its production tenfold to 30 000 FCEVs per year in 2020. Hyundai Motor has also stated plans to ramp up annual production to 40 000 FCEVs per year in 2022. FCEV costs are anticipated to fall with greater production; for example, a significant drop in fuel cell system costs is expected once annual production reaches 100 000 units. Raising the popularity of mid- and heavy-duty applications (in buses and trucks), especially in China, is essential to create sufficiently high demand. Expanding hydrogen refuelling infrastructure is also important to assuage consumers’ refuelling concerns. Recharging infrastructure deployment plans should focus on heavy-duty vehicles, as higher volumes can create a robust revenue stream. Reducing fuel cell costs by deploying more passenger vehicles, and hydrogen costs by putting more heavy-duty FCEVs on the road, would be a plausible approach to make FCEVs cost-competitive.

• The California Fuel Cell Partnership targets 1 million FCEVs in 2030.
• The Government of Korea announced a roadmap to produce 1.8 million fuel cells by 2030.
• The Japanese government has developed a revised roadmap to make FCEVs cost-competitive with hybrid vehicles around 2025. They target 800 000 FCEVs in 2030.
• Toyota plans to introduce 600 FCEV "Mirai" taxis in Paris by the end of 2020.
• The FCH-JU (Fuel Cell Hydrogen Joint Undertaking) is targeting fuel cell bus cost reductions through joint purchasing, and plans to introduce 360 fuel cell buses under the programme.
• China has a roadmap to deploy 50 000 FCEVs (including 10 000 commercial vehicles) in 2025 and 1 million in 2030.

Governments

Next 5-10 years:

• Support FCEV and hydrogen refuelling station incentives.
• Consider policies to decarbonise captive fleets (bus, taxi, truck).

Automotive industry

Next 5 years:

• Reduce fuel system and hydrogen storage tank costs.
• Expand FCEV model choices.
• Enhance technology collaboration among OEM's to accelerate FCEV deployment

Energy industry

Continuously:

• Continue hydrogen refuelling station deployment.

Gap 2. Deploying Electric Road System (ERS) corridors

With the exception of the long-range Tesla semi variant and the prototype Nikola trucks, the range of zero-emission trucks is limited to below 600 kilometres. Together with the time required to recharge depleted batteries (or the high amperage, voltage, and power draw requirements of very fast charging), this points to the need for alternative infrastructure and operational models for long-haul trucking. To date, three competitors seem most promising: dynamic charging on Electric Road System (ERS) corridors, continuing improvements in the performance, capacity, and costs of advanced lithium batteries, and hydrogen.

Conductive dynamic charging is much closer to market. Catenary systems have been operating for a few years, and are currently at TRL 6-7. In-road conductive systems, currently at TRL 5-6, are more expensive to build in existing roads, but may be cheaper to install at scale on new roads. Inductive charging, at TRL 4-5, is likely to be too costly relative to batteries and static charging solutions to merit adoption on any applications other than buses and heavily trafficked truck routes.

• Scania and Siemens began demonstration segments on stretches of highways in Sweden and Germany, and the length of trials in both countries has steadily increased. California started a trial in 2017 and in 2018 construction began on a trial in Northern Italy.
• The eRoadArlanda project, conceived by a consortium of public, private and research members, uses an in-road conductive charging system and a retractable arm extending from the bottom of a truck.
• The technology that is furthest from market uses induction coils and alternating electromagnetic fields to achieve contactless, inductive dynamic charging. Tests of technology have been limited; Utah State University publically demonstrated dynamic inductive charging on a test track in 2016, Qualcomm has successfully charged vehicles at 20 kW at highway speeds outside of Paris, and the Israeli company ElectRoad have tested a bus route outside of Tel Aviv.

The industry

• Develop further demonstration projects supplemented by studies using vehicle telematics

Governments and regulators

• Support and set up demonstration projects, for instance at ports
• Advance fiscal policy frameworks that e.g. tax diesel fuels and commercial trucks using the fuel, as well as road pricing measures. 
• Implement zero-emission vehicle (ZEV) mandates which can impel truck and bus makers to offer electric models. 

Next 5 to 10 years:

• Implement cost- and risk-sharing policies to address barriers that block initial deployment, financed by dedicated funding streams, such as fuel tax revenues, or other climate policy linked revenues

Gap 3. Improving the cost and performance of lithium-ion batteries

For trucks operating on regional delivery and long-haul segments, the suitability of electrification will depend upon continuing energy density improvements and cost reductions in lithium-based batteries.

There is a broad consensus that the ‘floor’ costs of current lithium-ion technologies may be around 80 USD/kWh. Going beyond that threshold is necessary in the SDS after around 2030, and will require the development of technologies that are currently in very early stages of development.

In long-haul, heavy-duty applications, gravimetric energy density is an important performance criterion on which advanced lithium-ion batteries will have to continue to improve in order to compete with fossil (diesel and natural gas) powered trucks. Advanced solid state chemistries may be able to achieve energy densities of 300-400 Wh/kg, and even more advanced chemistries (such as Lithium-Air) may have the potential to reach densities as high as 1000 Wh/kg or more. 

Digital technologies can be used to help integrate rail with other transport modes

Expanding high-quality urban rail transport depends on political champions, thorough project viability and costs assessments and effective funding, as much as it does on technical issues. Equally important are sound construction, installation of the necessary equipment and hardware, and well-managed operations.

Digital technologies can be used to help integrate rail with other transport modes, provide superior service and increase utilisation to raise revenues and reduce costs.

Gap 1. Digitalisation of rail: automation, management and control systems

By reducing the time and distance between trains, digital technologies can facilitate more intensive use of rail infrastructure, which increases capacity and boosts investment returns while improving user convenience and maintaining high safety standards.

Advanced traffic management and control systems (TRL 10) help ensure safe and efficient rail operations. These systems include Communication-Based Train Controls (CBTC), used extensively for urban rail, combined with Driver Assistance Systems (DAS) to maximise use of the network. These technologies can maximise network utilisation by reducing the headway between trains, and they have also demonstrated effectiveness in reducing energy consumption by up to 15% ( Dunbar, Roberts and Zhao, 2017 ).

Automated trains (TRL 9) promise improved safety, lower costs and greater energy efficiency than advanced traffic management and control systems. Under International Electrotechnical Commission (IEC) Standard No. 62267, the rail subsector defines Grades of Automation (GoA) ranging from fully manual operations, such as a tram-operating in street traffic (GoA-0), to unattended, fully automated operations (GoA-4). 

Other digital technologies such as big data analytics (TRL 9) and artificial intelligence (TRL 8) could significantly improve end-user services through seamless integration across different modes and other measures, and they could also improve energy efficiency and reduce costs for operators.

• The European Railway Traffic Management System (ERTMS), uses control, command, signalling and communication systems to ensure the interoperability of trains across the region, primarily on conventional and HSR networks.
• The first fully automated metro (GoA-4) opened in 1981 in Kobe, Japan, and there are now over 1 000 km of GoA-4 lines in 42 cities worldwide – around 7% of total installed metro networks ( UITP, 2018a ;  UITP, 2018b ). While the number of driverless metros is expanding rapidly on closed and secured lines, there are significant challenges to deploying fully autonomous trains on open, uncontrolled or unsecured lines (such as tram, intercity and freight lines). Nevertheless, a handful of autonomous tram-, intercity- and freight-line demonstration projects are in commercial operation.\

Gap 2. Establishing and expanding urban rail networks in existing and future large cities

A rich literature finds that the provision of reliable, convenient, and affordable public transit, and in the case of large cities, metro and light rail, not only reduces the per capita transport emissions in these cities, but can also contribute substantially to reducing levels of pollutants associated with road vehicles, and also enables reductions in the macro- and micro-economic costs of providing urban mobility.

Other studies identify economic and equity benefits that come from urban rail systems.

Even the more advanced technologies employed in rail, such as those covered in Gap 3, range in readiness from TRL: 10-11, as they have been widely rolled out.

Land value capture is a proven practice for securing capital to finance urban rail project construction, expansion and refurbishment, and operations. This opportunity arises where the rail transport network developers purchase land at pre-railway prices and develop residential, commercial and tertiary facilities, enabling them to capture the increase in property value induced by the railway operations. Governments may share in the risks and rewards by direct investment or through the taxation of higher value properties. The anticipated change in property value can mobilise debt financing. Such schemes have been used to finance urban rail projects in cities throughout the world.

• City governments: Integrate transport and land use planning divisions. Conduct feasibility studies to inform metro construction, improvement, and expansion plans, focusing on near-term (e.g. 10 years) and longer term (up to 30 years) potential. Develop appropriate plans to upgrade public transit (including BRT, bus, and rail), integrating analysis of co-benefits.
• Rail construction companies: Focus on strategies to incorporate energy-efficient and customer friendly technologies.
• Public transit operators: Identify operation strategies and technologies that can draw more customers, improve levels of service and reliability, and cut cost. Develop effective and informative public awareness and communication campaigns on the benefits of public transit.

Aviation is likely to be the most difficult transport sector to decarbonise.

The largest potential efficiency gains can be obtained by completely redesigning aircraft. Considering the long lead times and investment required, such measures are unlikely to be commercialised by 2030. However, “clean sheet” wing and tube aircraft have the potential to reduce fuel burn by 40% (Kharina, 2017).

In addition to research and trials of new, more efficient aircraft designs, adoption of alternative, low-carbon jet fuels will be needed to reduce CO 2  emissions. Technology and scale-up barriers in producing such fuels can be best addressed through direct support from governments, incentives and standards.

Nearer term solutions, such as improving flight routing systems and switching to hydrogen and/or electricity during taxiing, can also improve the overall efficiency of the sector. 

Gap 1. Shortening flight distances through better routing

Considerable fuel is wasted due to inefficient routing. While providing the same service, better flight routing could limit inefficient passenger activity growth and cut consumption by as much as 10% (IEA, 2018).

• The European Space Agency’s IRIS Programme is a new technology for routing aircraft that uses satellites to complement traditional radio transmission for air traffic management. As aircraft currently have to fly over ‘checkpoints’ to interact with ground-based radio transmissions, they often cannot take the shortest route between airports, adding an average 42 km to each flight. By using satellite navigation, however, IRIS will be better able to route flights and manage congestion in the skies. These routing improvements are projected to reduce fuel use by 5‑10% for a typical European journey (SESAR, 2015).
• A similar scheme to improve aircraft routing was introduced in 2018 by ENAV, the Italian agency overseeing flight routing. It frees aircraft flying above 9 000 m to take a more efficient route than normal, saving an estimated 22.8 km per flight and a total of 37 000 tonnes of fuel and 116 000 tonnes of CO2 in 2017 (ENAV, 2018).

Low and zero-carbon fuels barely figure in the maritime fuel mix

To put international shipping on the SDS trajectory, it is essential to switch to low- and zero-carbon fuels, as they barely figure in the maritime fuel mix.

Interest in using alternative fuels such as ammonia, hydrogen or advanced biodiesel and ammonia mounted significantly after the IMO adopted its initial strategy to reduce GHG emissions from ships by 2050. This agreement happened shortly before the implementation of Emission Control Areas (which limit sulphur oxide [SOx] and particulate matter [PM] emissions near ports) and tighter sulphur emission regulations, which will come into force in 2020.

Although advanced biofuels, hydrogen and ammonia are potential low-carbon options to replace conventional fuels, an important uptake barrier is their high cost compared with conventional fuels. In the cases of ammonia and hydrogen, another barrier is the lack of infrastructure.

Gap 1: Transitioning to low-carbon ammonia or hydrogen fuel

In addition to diversifying the sources of maritime fuel supplies, adopting alternative fuels would help meet the tighter sulphur standards coming into effect in 2020; alternatives to bunker fuel will also be needed to meet SOx and PM emissions limits near a growing number of the world's ports (Emission Control Areas). These near-term air pollution targets can generally be met by switching to low-sulphur diesel or investing in scrubbers, and liquefied natural gas (LNG) is also an option because it does not emit SOx.

Oil demand in this fast-growing sector is set to rise 20% (to 6 million barrels per day) by 2030 unless measures are taken to enforce the IMO’s long-term GHG emissions target. Ship owners must therefore make some important decisions very soon.

In the long term, GHG emissions from international shipping must be cut by at least 50% by 2050. A challenge to meeting this IMO target is that ship lifetimes generally span two to three decades. However, depending on eventual costs and incentives, using ammonia or hydrogen could be a solution.

Current deployment plans for ammonia or hydrogen focus on relatively small-scale applications, but there is considerable scope for direct and indirect hydrogen use in shipping.

Using hydrogen and ammonia in shipping is especially advantageous because of port infrastructure, particularly when ports are linked with large industrial clusters that have on-site refineries or chemical facilities that already use and produce hydrogen. Scaling up hydrogen (and ammonia) production in such coastal industrial hubs would therefore provide alternative fuel for ships, and these ships could then be used to deliver hydrogen to other parts of the world, establishing maritime trade routes for potentially larger future demand.

A few smaller ships have been equipped with fuel cells in the 100‑kilowatt (kW) to 300‑kW range. Fuel cell applications with low electrical power output (up to 100 kW) have also been deployed in maritime applications ( DNV GL, 2018 ); these rely mostly on PEMFC technology ( E4tech, 2018 ). Fuel cell technologies are currently at TRL-4.

In the near to medium term, implicit or explicit carbon pricing or mandates will be necessary to promote the development and adoption of low-carbon fuel alternatives in shipping. Ammonia produced through low- or zero-carbon methods and used on ships with conventional internal combustion engines currently appears to be the most cost-competitive option. The carbon price needed to make this option break even with very-low-sulphur oil (VLSFO) is highly sensitive to the delivered cost of hydrogen to make ammonia, which is determined by the cost of producing it with a steam methane reformer (SMR) fitted with carbon capture and storage (CCS), and/or electricity costs for hydrogen production via electrolysis. Reducing ammonia and hydrogen supply costs at each step of the value chain will be critical to make these low- and zero-carbon fuels competitive.

Subscription successful

Thank you for subscribing. You can unsubscribe at any time by clicking the link at the bottom of any IEA newsletter.

• Search Menu
• Sign in through your institution
• Browse content in A - General Economics and Teaching
• Browse content in A1 - General Economics
• A10 - General
• A11 - Role of Economics; Role of Economists; Market for Economists
• A12 - Relation of Economics to Other Disciplines
• A13 - Relation of Economics to Social Values
• A14 - Sociology of Economics
• Browse content in A2 - Economic Education and Teaching of Economics
• A20 - General
• A29 - Other
• A3 - Collective Works
• Browse content in B - History of Economic Thought, Methodology, and Heterodox Approaches
• Browse content in B0 - General
• B00 - General
• Browse content in B1 - History of Economic Thought through 1925
• B10 - General
• B11 - Preclassical (Ancient, Medieval, Mercantilist, Physiocratic)
• B12 - Classical (includes Adam Smith)
• B13 - Neoclassical through 1925 (Austrian, Marshallian, Walrasian, Stockholm School)
• B14 - Socialist; Marxist
• B15 - Historical; Institutional; Evolutionary
• B16 - History of Economic Thought: Quantitative and Mathematical
• B17 - International Trade and Finance
• B19 - Other
• Browse content in B2 - History of Economic Thought since 1925
• B20 - General
• B21 - Microeconomics
• B22 - Macroeconomics
• B23 - Econometrics; Quantitative and Mathematical Studies
• B24 - Socialist; Marxist; Sraffian
• B25 - Historical; Institutional; Evolutionary; Austrian
• B26 - Financial Economics
• B27 - International Trade and Finance
• B29 - Other
• Browse content in B3 - History of Economic Thought: Individuals
• B30 - General
• B31 - Individuals
• Browse content in B4 - Economic Methodology
• B40 - General
• B41 - Economic Methodology
• B49 - Other
• Browse content in B5 - Current Heterodox Approaches
• B50 - General
• B51 - Socialist; Marxian; Sraffian
• B52 - Institutional; Evolutionary
• B53 - Austrian
• B54 - Feminist Economics
• B55 - Social Economics
• B59 - Other
• Browse content in C - Mathematical and Quantitative Methods
• Browse content in C0 - General
• C00 - General
• C02 - Mathematical Methods
• Browse content in C1 - Econometric and Statistical Methods and Methodology: General
• C10 - General
• C12 - Hypothesis Testing: General
• C13 - Estimation: General
• C14 - Semiparametric and Nonparametric Methods: General
• C18 - Methodological Issues: General
• C19 - Other
• Browse content in C2 - Single Equation Models; Single Variables
• C20 - General
• C21 - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions
• C22 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
• C23 - Panel Data Models; Spatio-temporal Models
• C25 - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
• Browse content in C3 - Multiple or Simultaneous Equation Models; Multiple Variables
• C30 - General
• C32 - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
• C34 - Truncated and Censored Models; Switching Regression Models
• C38 - Classification Methods; Cluster Analysis; Principal Components; Factor Models
• Browse content in C4 - Econometric and Statistical Methods: Special Topics
• C43 - Index Numbers and Aggregation
• C44 - Operations Research; Statistical Decision Theory
• Browse content in C5 - Econometric Modeling
• C50 - General
• Browse content in C6 - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
• C60 - General
• C61 - Optimization Techniques; Programming Models; Dynamic Analysis
• C62 - Existence and Stability Conditions of Equilibrium
• C63 - Computational Techniques; Simulation Modeling
• C65 - Miscellaneous Mathematical Tools
• C67 - Input-Output Models
• Browse content in C8 - Data Collection and Data Estimation Methodology; Computer Programs
• C82 - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
• C89 - Other
• Browse content in C9 - Design of Experiments
• C90 - General
• C91 - Laboratory, Individual Behavior
• C92 - Laboratory, Group Behavior
• C93 - Field Experiments
• Browse content in D - Microeconomics
• Browse content in D0 - General
• D01 - Microeconomic Behavior: Underlying Principles
• D02 - Institutions: Design, Formation, Operations, and Impact
• D03 - Behavioral Microeconomics: Underlying Principles
• Browse content in D1 - Household Behavior and Family Economics
• D10 - General
• D11 - Consumer Economics: Theory
• D12 - Consumer Economics: Empirical Analysis
• D13 - Household Production and Intrahousehold Allocation
• D14 - Household Saving; Personal Finance
• Browse content in D2 - Production and Organizations
• D20 - General
• D21 - Firm Behavior: Theory
• D22 - Firm Behavior: Empirical Analysis
• D23 - Organizational Behavior; Transaction Costs; Property Rights
• D24 - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
• D25 - Intertemporal Firm Choice: Investment, Capacity, and Financing
• Browse content in D3 - Distribution
• D30 - General
• D31 - Personal Income, Wealth, and Their Distributions
• D33 - Factor Income Distribution
• D39 - Other
• Browse content in D4 - Market Structure, Pricing, and Design
• D40 - General
• D41 - Perfect Competition
• D42 - Monopoly
• D43 - Oligopoly and Other Forms of Market Imperfection
• D46 - Value Theory
• Browse content in D5 - General Equilibrium and Disequilibrium
• D50 - General
• D51 - Exchange and Production Economies
• D57 - Input-Output Tables and Analysis
• D58 - Computable and Other Applied General Equilibrium Models
• Browse content in D6 - Welfare Economics
• D60 - General
• D61 - Allocative Efficiency; Cost-Benefit Analysis
• D62 - Externalities
• D63 - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
• D64 - Altruism; Philanthropy
• D69 - Other
• Browse content in D7 - Analysis of Collective Decision-Making
• D71 - Social Choice; Clubs; Committees; Associations
• D72 - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
• D73 - Bureaucracy; Administrative Processes in Public Organizations; Corruption
• D74 - Conflict; Conflict Resolution; Alliances; Revolutions
• Browse content in D8 - Information, Knowledge, and Uncertainty
• D80 - General
• D81 - Criteria for Decision-Making under Risk and Uncertainty
• D82 - Asymmetric and Private Information; Mechanism Design
• D83 - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
• D84 - Expectations; Speculations
• D85 - Network Formation and Analysis: Theory
• D86 - Economics of Contract: Theory
• D87 - Neuroeconomics
• Browse content in D9 - Micro-Based Behavioral Economics
• D91 - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
• Browse content in E - Macroeconomics and Monetary Economics
• Browse content in E0 - General
• E00 - General
• E01 - Measurement and Data on National Income and Product Accounts and Wealth; Environmental Accounts
• E02 - Institutions and the Macroeconomy
• Browse content in E1 - General Aggregative Models
• E10 - General
• E11 - Marxian; Sraffian; Kaleckian
• E12 - Keynes; Keynesian; Post-Keynesian
• E13 - Neoclassical
• E16 - Social Accounting Matrix
• E17 - Forecasting and Simulation: Models and Applications
• Browse content in E2 - Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy
• E20 - General
• E21 - Consumption; Saving; Wealth
• E22 - Investment; Capital; Intangible Capital; Capacity
• E23 - Production
• E24 - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
• E25 - Aggregate Factor Income Distribution
• E26 - Informal Economy; Underground Economy
• E27 - Forecasting and Simulation: Models and Applications
• Browse content in E3 - Prices, Business Fluctuations, and Cycles
• E30 - General
• E31 - Price Level; Inflation; Deflation
• E32 - Business Fluctuations; Cycles
• E37 - Forecasting and Simulation: Models and Applications
• Browse content in E4 - Money and Interest Rates
• E40 - General
• E41 - Demand for Money
• E42 - Monetary Systems; Standards; Regimes; Government and the Monetary System; Payment Systems
• E43 - Interest Rates: Determination, Term Structure, and Effects
• E44 - Financial Markets and the Macroeconomy
• E49 - Other
• Browse content in E5 - Monetary Policy, Central Banking, and the Supply of Money and Credit
• E50 - General
• E51 - Money Supply; Credit; Money Multipliers
• E52 - Monetary Policy
• E58 - Central Banks and Their Policies
• Browse content in E6 - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook
• E60 - General
• E61 - Policy Objectives; Policy Designs and Consistency; Policy Coordination
• E62 - Fiscal Policy
• E63 - Comparative or Joint Analysis of Fiscal and Monetary Policy; Stabilization; Treasury Policy
• E64 - Incomes Policy; Price Policy
• E65 - Studies of Particular Policy Episodes
• Browse content in F - International Economics
• Browse content in F0 - General
• F00 - General
• F01 - Global Outlook
• F02 - International Economic Order and Integration
• Browse content in F1 - Trade
• F10 - General
• F11 - Neoclassical Models of Trade
• F12 - Models of Trade with Imperfect Competition and Scale Economies; Fragmentation
• F13 - Trade Policy; International Trade Organizations
• F14 - Empirical Studies of Trade
• F15 - Economic Integration
• F16 - Trade and Labor Market Interactions
• F17 - Trade Forecasting and Simulation
• F18 - Trade and Environment
• Browse content in F2 - International Factor Movements and International Business
• F20 - General
• F21 - International Investment; Long-Term Capital Movements
• F22 - International Migration
• F23 - Multinational Firms; International Business
• Browse content in F3 - International Finance
• F30 - General
• F31 - Foreign Exchange
• F32 - Current Account Adjustment; Short-Term Capital Movements
• F33 - International Monetary Arrangements and Institutions
• F34 - International Lending and Debt Problems
• F35 - Foreign Aid
• F36 - Financial Aspects of Economic Integration
• F37 - International Finance Forecasting and Simulation: Models and Applications
• F39 - Other
• Browse content in F4 - Macroeconomic Aspects of International Trade and Finance
• F40 - General
• F41 - Open Economy Macroeconomics
• F42 - International Policy Coordination and Transmission
• F43 - Economic Growth of Open Economies
• F44 - International Business Cycles
• F45 - Macroeconomic Issues of Monetary Unions
• F47 - Forecasting and Simulation: Models and Applications
• Browse content in F5 - International Relations, National Security, and International Political Economy
• F50 - General
• F51 - International Conflicts; Negotiations; Sanctions
• F53 - International Agreements and Observance; International Organizations
• F54 - Colonialism; Imperialism; Postcolonialism
• F55 - International Institutional Arrangements
• F59 - Other
• Browse content in F6 - Economic Impacts of Globalization
• F60 - General
• F61 - Microeconomic Impacts
• F62 - Macroeconomic Impacts
• F63 - Economic Development
• F64 - Environment
• F65 - Finance
• Browse content in G - Financial Economics
• Browse content in G0 - General
• G00 - General
• G01 - Financial Crises
• Browse content in G1 - General Financial Markets
• G10 - General
• G11 - Portfolio Choice; Investment Decisions
• G12 - Asset Pricing; Trading volume; Bond Interest Rates
• G13 - Contingent Pricing; Futures Pricing
• G14 - Information and Market Efficiency; Event Studies; Insider Trading
• G15 - International Financial Markets
• G18 - Government Policy and Regulation
• G19 - Other
• Browse content in G2 - Financial Institutions and Services
• G20 - General
• G21 - Banks; Depository Institutions; Micro Finance Institutions; Mortgages
• G22 - Insurance; Insurance Companies; Actuarial Studies
• G23 - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
• G24 - Investment Banking; Venture Capital; Brokerage; Ratings and Ratings Agencies
• G28 - Government Policy and Regulation
• Browse content in G3 - Corporate Finance and Governance
• G30 - General
• G32 - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill
• G33 - Bankruptcy; Liquidation
• G34 - Mergers; Acquisitions; Restructuring; Corporate Governance
• G35 - Payout Policy
• G38 - Government Policy and Regulation
• Browse content in G5 - Household Finance
• G51 - Household Saving, Borrowing, Debt, and Wealth
• Browse content in H - Public Economics
• Browse content in H1 - Structure and Scope of Government
• H10 - General
• H11 - Structure, Scope, and Performance of Government
• H12 - Crisis Management
• Browse content in H2 - Taxation, Subsidies, and Revenue
• H20 - General
• H22 - Incidence
• H23 - Externalities; Redistributive Effects; Environmental Taxes and Subsidies
• H25 - Business Taxes and Subsidies
• H26 - Tax Evasion and Avoidance
• Browse content in H3 - Fiscal Policies and Behavior of Economic Agents
• Browse content in H4 - Publicly Provided Goods
• H40 - General
• H41 - Public Goods
• Browse content in H5 - National Government Expenditures and Related Policies
• H50 - General
• H53 - Government Expenditures and Welfare Programs
• H55 - Social Security and Public Pensions
• H56 - National Security and War
• Browse content in H6 - National Budget, Deficit, and Debt
• H60 - General
• H62 - Deficit; Surplus
• H63 - Debt; Debt Management; Sovereign Debt
• H68 - Forecasts of Budgets, Deficits, and Debt
• Browse content in H7 - State and Local Government; Intergovernmental Relations
• H70 - General
• H74 - State and Local Borrowing
• H77 - Intergovernmental Relations; Federalism; Secession
• Browse content in I - Health, Education, and Welfare
• Browse content in I0 - General
• I00 - General
• Browse content in I1 - Health
• I10 - General
• I12 - Health Behavior
• I14 - Health and Inequality
• I15 - Health and Economic Development
• Browse content in I2 - Education and Research Institutions
• I20 - General
• I21 - Analysis of Education
• I23 - Higher Education; Research Institutions
• I24 - Education and Inequality
• I26 - Returns to Education
• Browse content in I3 - Welfare, Well-Being, and Poverty
• I30 - General
• I31 - General Welfare
• I32 - Measurement and Analysis of Poverty
• I38 - Government Policy; Provision and Effects of Welfare Programs
• Browse content in J - Labor and Demographic Economics
• Browse content in J0 - General
• J00 - General
• J01 - Labor Economics: General
• J08 - Labor Economics Policies
• Browse content in J1 - Demographic Economics
• J10 - General
• J13 - Fertility; Family Planning; Child Care; Children; Youth
• J15 - Economics of Minorities, Races, Indigenous Peoples, and Immigrants; Non-labor Discrimination
• J16 - Economics of Gender; Non-labor Discrimination
• J18 - Public Policy
• Browse content in J2 - Demand and Supply of Labor
• J20 - General
• J21 - Labor Force and Employment, Size, and Structure
• J22 - Time Allocation and Labor Supply
• J23 - Labor Demand
• J24 - Human Capital; Skills; Occupational Choice; Labor Productivity
• J26 - Retirement; Retirement Policies
• J28 - Safety; Job Satisfaction; Related Public Policy
• J29 - Other
• Browse content in J3 - Wages, Compensation, and Labor Costs
• J30 - General
• J31 - Wage Level and Structure; Wage Differentials
• J32 - Nonwage Labor Costs and Benefits; Retirement Plans; Private Pensions
• J33 - Compensation Packages; Payment Methods
• J38 - Public Policy
• Browse content in J4 - Particular Labor Markets
• J40 - General
• J41 - Labor Contracts
• J42 - Monopsony; Segmented Labor Markets
• J44 - Professional Labor Markets; Occupational Licensing
• J45 - Public Sector Labor Markets
• J46 - Informal Labor Markets
• J48 - Public Policy
• J49 - Other
• Browse content in J5 - Labor-Management Relations, Trade Unions, and Collective Bargaining
• J50 - General
• J51 - Trade Unions: Objectives, Structure, and Effects
• J52 - Dispute Resolution: Strikes, Arbitration, and Mediation; Collective Bargaining
• J53 - Labor-Management Relations; Industrial Jurisprudence
• J54 - Producer Cooperatives; Labor Managed Firms; Employee Ownership
• J58 - Public Policy
• Browse content in J6 - Mobility, Unemployment, Vacancies, and Immigrant Workers
• J60 - General
• J61 - Geographic Labor Mobility; Immigrant Workers
• J62 - Job, Occupational, and Intergenerational Mobility
• J63 - Turnover; Vacancies; Layoffs
• J64 - Unemployment: Models, Duration, Incidence, and Job Search
• J65 - Unemployment Insurance; Severance Pay; Plant Closings
• J68 - Public Policy
• J69 - Other
• Browse content in J7 - Labor Discrimination
• J71 - Discrimination
• J78 - Public Policy
• Browse content in J8 - Labor Standards: National and International
• J80 - General
• J81 - Working Conditions
• J83 - Workers' Rights
• J88 - Public Policy
• Browse content in K - Law and Economics
• Browse content in K0 - General
• K00 - General
• Browse content in K1 - Basic Areas of Law
• K11 - Property Law
• K12 - Contract Law
• K13 - Tort Law and Product Liability; Forensic Economics
• Browse content in K2 - Regulation and Business Law
• K20 - General
• K21 - Antitrust Law
• K22 - Business and Securities Law
• K23 - Regulated Industries and Administrative Law
• K25 - Real Estate Law
• Browse content in K3 - Other Substantive Areas of Law
• K31 - Labor Law
• K39 - Other
• Browse content in K4 - Legal Procedure, the Legal System, and Illegal Behavior
• K40 - General
• K41 - Litigation Process
• K42 - Illegal Behavior and the Enforcement of Law
• Browse content in L - Industrial Organization
• Browse content in L0 - General
• L00 - General
• Browse content in L1 - Market Structure, Firm Strategy, and Market Performance
• L10 - General
• L11 - Production, Pricing, and Market Structure; Size Distribution of Firms
• L12 - Monopoly; Monopolization Strategies
• L13 - Oligopoly and Other Imperfect Markets
• L14 - Transactional Relationships; Contracts and Reputation; Networks
• L16 - Industrial Organization and Macroeconomics: Industrial Structure and Structural Change; Industrial Price Indices
• Browse content in L2 - Firm Objectives, Organization, and Behavior
• L20 - General
• L21 - Business Objectives of the Firm
• L22 - Firm Organization and Market Structure
• L23 - Organization of Production
• L24 - Contracting Out; Joint Ventures; Technology Licensing
• L25 - Firm Performance: Size, Diversification, and Scope
• L26 - Entrepreneurship
• L29 - Other
• Browse content in L3 - Nonprofit Organizations and Public Enterprise
• L30 - General
• L31 - Nonprofit Institutions; NGOs; Social Entrepreneurship
• L32 - Public Enterprises; Public-Private Enterprises
• L33 - Comparison of Public and Private Enterprises and Nonprofit Institutions; Privatization; Contracting Out
• L39 - Other
• Browse content in L4 - Antitrust Issues and Policies
• L40 - General
• L41 - Monopolization; Horizontal Anticompetitive Practices
• L44 - Antitrust Policy and Public Enterprises, Nonprofit Institutions, and Professional Organizations
• Browse content in L5 - Regulation and Industrial Policy
• L50 - General
• L52 - Industrial Policy; Sectoral Planning Methods
• Browse content in L6 - Industry Studies: Manufacturing
• L60 - General
• L61 - Metals and Metal Products; Cement; Glass; Ceramics
• L66 - Food; Beverages; Cosmetics; Tobacco; Wine and Spirits
• L67 - Other Consumer Nondurables: Clothing, Textiles, Shoes, and Leather Goods; Household Goods; Sports Equipment
• Browse content in L7 - Industry Studies: Primary Products and Construction
• L78 - Government Policy
• Browse content in L8 - Industry Studies: Services
• L80 - General
• L82 - Entertainment; Media
• Browse content in L9 - Industry Studies: Transportation and Utilities
• L97 - Utilities: General
• L98 - Government Policy
• Browse content in M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
• Browse content in M0 - General
• M00 - General
• Browse content in M1 - Business Administration
• M10 - General
• M12 - Personnel Management; Executives; Executive Compensation
• M13 - New Firms; Startups
• M16 - International Business Administration
• Browse content in M2 - Business Economics
• M21 - Business Economics
• Browse content in M3 - Marketing and Advertising
• M37 - Advertising
• Browse content in M4 - Accounting and Auditing
• M41 - Accounting
• M49 - Other
• Browse content in M5 - Personnel Economics
• M51 - Firm Employment Decisions; Promotions
• M52 - Compensation and Compensation Methods and Their Effects
• M54 - Labor Management
• M55 - Labor Contracting Devices
• Browse content in N - Economic History
• Browse content in N0 - General
• N00 - General
• N01 - Development of the Discipline: Historiographical; Sources and Methods
• Browse content in N1 - Macroeconomics and Monetary Economics; Industrial Structure; Growth; Fluctuations
• N10 - General, International, or Comparative
• N11 - U.S.; Canada: Pre-1913
• N12 - U.S.; Canada: 1913-
• N13 - Europe: Pre-1913
• N14 - Europe: 1913-
• N15 - Asia including Middle East
• N17 - Africa; Oceania
• Browse content in N2 - Financial Markets and Institutions
• N20 - General, International, or Comparative
• N23 - Europe: Pre-1913
• N24 - Europe: 1913-
• N25 - Asia including Middle East
• N26 - Latin America; Caribbean
• Browse content in N3 - Labor and Consumers, Demography, Education, Health, Welfare, Income, Wealth, Religion, and Philanthropy
• N30 - General, International, or Comparative
• N32 - U.S.; Canada: 1913-
• N34 - Europe: 1913-
• Browse content in N4 - Government, War, Law, International Relations, and Regulation
• N43 - Europe: Pre-1913
• Browse content in N5 - Agriculture, Natural Resources, Environment, and Extractive Industries
• N50 - General, International, or Comparative
• N51 - U.S.; Canada: Pre-1913
• N52 - U.S.; Canada: 1913-
• N55 - Asia including Middle East
• N7 - Transport, Trade, Energy, Technology, and Other Services
• Browse content in N8 - Micro-Business History
• N80 - General, International, or Comparative
• Browse content in O - Economic Development, Innovation, Technological Change, and Growth
• Browse content in O1 - Economic Development
• O10 - General
• O11 - Macroeconomic Analyses of Economic Development
• O12 - Microeconomic Analyses of Economic Development
• O13 - Agriculture; Natural Resources; Energy; Environment; Other Primary Products
• O14 - Industrialization; Manufacturing and Service Industries; Choice of Technology
• O15 - Human Resources; Human Development; Income Distribution; Migration
• O16 - Financial Markets; Saving and Capital Investment; Corporate Finance and Governance
• O17 - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements
• O18 - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure
• O19 - International Linkages to Development; Role of International Organizations
• Browse content in O2 - Development Planning and Policy
• O20 - General
• O23 - Fiscal and Monetary Policy in Development
• O24 - Trade Policy; Factor Movement Policy; Foreign Exchange Policy
• O25 - Industrial Policy
• Browse content in O3 - Innovation; Research and Development; Technological Change; Intellectual Property Rights
• O30 - General
• O31 - Innovation and Invention: Processes and Incentives
• O32 - Management of Technological Innovation and R&D
• O33 - Technological Change: Choices and Consequences; Diffusion Processes
• O34 - Intellectual Property and Intellectual Capital
• O35 - Social Innovation
• O38 - Government Policy
• O39 - Other
• Browse content in O4 - Economic Growth and Aggregate Productivity
• O40 - General
• O41 - One, Two, and Multisector Growth Models
• O43 - Institutions and Growth
• O44 - Environment and Growth
• O47 - Empirical Studies of Economic Growth; Aggregate Productivity; Cross-Country Output Convergence
• Browse content in O5 - Economywide Country Studies
• O50 - General
• O51 - U.S.; Canada
• O52 - Europe
• O53 - Asia including Middle East
• O54 - Latin America; Caribbean
• O55 - Africa
• Browse content in P - Economic Systems
• Browse content in P0 - General
• P00 - General
• Browse content in P1 - Capitalist Systems
• P10 - General
• P11 - Planning, Coordination, and Reform
• P12 - Capitalist Enterprises
• P13 - Cooperative Enterprises
• P14 - Property Rights
• P16 - Political Economy
• P17 - Performance and Prospects
• Browse content in P2 - Socialist Systems and Transitional Economies
• P20 - General
• P21 - Planning, Coordination, and Reform
• P25 - Urban, Rural, and Regional Economics
• Browse content in P3 - Socialist Institutions and Their Transitions
• P30 - General
• P31 - Socialist Enterprises and Their Transitions
• P32 - Collectives; Communes; Agriculture
• P35 - Public Economics
• P36 - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty
• P37 - Legal Institutions; Illegal Behavior
• Browse content in P4 - Other Economic Systems
• P40 - General
• P41 - Planning, Coordination, and Reform
• P46 - Consumer Economics; Health; Education and Training; Welfare, Income, Wealth, and Poverty
• P48 - Political Economy; Legal Institutions; Property Rights; Natural Resources; Energy; Environment; Regional Studies
• Browse content in P5 - Comparative Economic Systems
• P50 - General
• P51 - Comparative Analysis of Economic Systems
• P52 - Comparative Studies of Particular Economies
• Browse content in Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
• Browse content in Q0 - General
• Q00 - General
• Q01 - Sustainable Development
• Browse content in Q1 - Agriculture
• Q15 - Land Ownership and Tenure; Land Reform; Land Use; Irrigation; Agriculture and Environment
• Q18 - Agricultural Policy; Food Policy
• Browse content in Q3 - Nonrenewable Resources and Conservation
• Q30 - General
• Browse content in Q4 - Energy
• Q41 - Demand and Supply; Prices
• Q42 - Alternative Energy Sources
• Q48 - Government Policy
• Browse content in Q5 - Environmental Economics
• Q50 - General
• Q54 - Climate; Natural Disasters; Global Warming
• Q56 - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
• Q57 - Ecological Economics: Ecosystem Services; Biodiversity Conservation; Bioeconomics; Industrial Ecology
• Browse content in R - Urban, Rural, Regional, Real Estate, and Transportation Economics
• Browse content in R0 - General
• R00 - General
• Browse content in R1 - General Regional Economics
• R10 - General
• R11 - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
• R12 - Size and Spatial Distributions of Regional Economic Activity
• R15 - Econometric and Input-Output Models; Other Models
• Browse content in R2 - Household Analysis
• R20 - General
• Browse content in R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location
• R30 - General
• R31 - Housing Supply and Markets
• R4 - Transportation Economics
• Browse content in R5 - Regional Government Analysis
• R51 - Finance in Urban and Rural Economies
• R58 - Regional Development Planning and Policy
• Browse content in Y - Miscellaneous Categories
• Browse content in Y1 - Data: Tables and Charts
• Y10 - Data: Tables and Charts
• Browse content in Y3 - Book Reviews (unclassified)
• Y30 - Book Reviews (unclassified)
• Browse content in Y8 - Related Disciplines
• Y80 - Related Disciplines
• Browse content in Z - Other Special Topics
• Browse content in Z0 - General
• Z00 - General
• Browse content in Z1 - Cultural Economics; Economic Sociology; Economic Anthropology
• Z10 - General
• Z11 - Economics of the Arts and Literature
• Z12 - Religion
• Z13 - Economic Sociology; Economic Anthropology; Social and Economic Stratification
• Z18 - Public Policy
• Browse content in Z2 - Sports Economics
• Z29 - Other
• Advance articles
• Editor's Choice
• Author Guidelines
• Submission Site
• Open Access
• About Cambridge Journal of Economics
• About the Cambridge Political Economy Society
• Editorial Board
• Advertising and Corporate Services
• Self-Archiving Policy
• Dispatch Dates
• Terms and Conditions
• Journals on Oxford Academic
• Books on Oxford Academic

Article Contents

1. introduction, 2. paris purposes and the future we made, 3. the problem of unmaking, 4. conclusion: unmaking and is paris possible, conflict of interest statement, bibliography.

• < Previous

Electric vehicles: the future we made and the problem of unmaking it

• Article contents
• Figures & tables
• Supplementary Data

Jamie Morgan, Electric vehicles: the future we made and the problem of unmaking it, Cambridge Journal of Economics , Volume 44, Issue 4, July 2020, Pages 953–977, https://doi.org/10.1093/cje/beaa022

• Permissions Icon Permissions

The uptake of battery electric vehicles (BEVs), subject to bottlenecks, seems to have reached a tipping point in the UK and this mirrors a general trend globally. BEVs are being positioned as one significant strand in the web of policy intended to translate the good intentions of Article 2 of the Conference of the Parties 21 Paris Agreement into reality. Governments and municipalities are anticipating that a widespread shift to BEVs will significantly reduce transport-related carbon emissions and, therefore, augment their nationally determined contributions to emissions reduction within the Paris Agreement. However, matters are more complicated than they may appear. There is a difference between thinking we can just keep relying on human ingenuity to solve problems after they emerge and engaging in fundamental social redesign to prevent the trajectories of harm. BEVs illustrate this. The contribution to emissions reduction per vehicle unit may be less than the public initially perceive since the important issue here is the lifecycle of the BEV and this is in no sense zero-emission. Furthermore, even though one can make the case that BEVs are a superior alternative to the fossil fuel-powered internal combustion engine, the transition to BEVs may actually facilitate exceeding the carbon budget on which the Paris Agreement ultimately rests. Whether in fact it does depends on the nature of the policy that shapes the transition. If the transition is a form of substitution that conforms to rather than shifts against current global scales and trends in private transportation, then it is highly likely that BEVs will be a successful failure. For this not to be the case, then the transition to BEVs must be coordinated with a transformation of the current scales and trends in private transportation. That is, a significant reduction in dependence on and individual ownership of powered vehicles, a radical reimagining of the nature of private conveyance and of public transportation.

According to the UK Society of Motor Manufacturers and Traders (SMMT), the Tesla Model 3 sold 2,685 units in December 2019, making it the 9th best-selling car in the country in that month (by new registrations; in August, a typically slow month for sales, it had been 3rd with 2,082 units sold; Lea, 2019; SMMT, 2019 ). As of early 2020, battery electric vehicles (BEVs) such as the new Hyundai Electric Kona had a two-year waiting list for delivery and the Kia e-Niro a one-year wait. The uptake of electric vehicles, subject to bottlenecks, seems to have reached a tipping point in the UK and this transcends the popularity of any given model. This possible tipping point mirrors a general trend globally (however, see later for quite what this means). At the regional, national and municipal scale, public health and environmentally informed legislation are encouraging vehicle manufacturers to invest heavily in alternative fuel vehicles and, in particular, BEVs and plug-in hybrid vehicles (PHEVs), which are jointly categorised within ‘ultra-low emission vehicles’ (ULEVs). 1 According to a report by Deloitte, more than 20 major cities worldwide announced plans in 2017–18 to ban petrol and diesel cars by 2030 or sooner ( Deloitte, 2018 , p. 5). All the major manufacturers have or are launching BEV models, and so vehicles are becoming available across the status and income spectrum that has in the past determined market segmentation. According to the consultancy Frost & Sullivan (2019) , there were 207 models (143 BEVs, 64 PHEVs) available globally in 2018 compared with 165 in 2017.

In 2018, the UK government published its Road to Zero policy commitment and introduced the Automated and Electric Vehicles Act 2018 , which empowers future governments to regulate regarding the required infrastructure. Road to Zero announced an ‘expectation’ that between 50% and 70% of new cars and vans will be electric by 2030 and the intention to ‘end the sale of new conventional petrol and diesel cars and vans by 2040’, with the ‘ambition’ that by 2050 almost all vehicles on the road will be ‘zero-emission’ at the point of use ( Department for Transport, 2018 ). Progress towards these goals was to be reviewed 2025. 2 However, on 4 February 2020, Prime Minister Boris Johnson announced that in the run-up to Conference of the Parties (COP)26 in Glasgow (now postponed), Britain would bring forward its 2040 goal to 2035. The UK is a member of the Clean Energy Ministerial Campaign (CEM), which launched the EV30@30 initiative in 2017, and its Road to Zero policy commitments broadly align with those of many European countries. 3 Norway has longstanding generous incentives for BEVs ( Holtsmark and Skonhoft, 2014 ) and 31% of all cars sold in 2018 and just under 50% in the first half of 2019 in Norway were BEVs. According to the International Energy Agency (IEA), Norway is the per capita global leader in electric vehicle uptake ( IEA, 2019A ). 4

BEVs, then, are being positioned as one significant strand in the web of policy intended to translate the good intentions of Article 2 of the COP 21 Paris Agreement into reality (see Morgan, 2016 ; IEA, 2019A , pp. 11–2). Clearly, governments and municipalities are anticipating that a widespread shift to electric vehicles will significantly reduce transport-related carbon emissions and, therefore, augment their nationally determined contributions (NDCs) to emissions reduction within the Paris Agreement. And, since the BEV trend is global, the impacts potentially also apply to countries whose relation to Paris is more problematic, including the USA (for Trump and his context, see Gills et al. , 2019 ). However, matters are more complicated than they may appear. Clearly, innovation and technological change are important components in our response to the challenge of climate change. However, there is a difference between thinking we can just keep relying on human ingenuity to solve problems after they emerge and engaging in fundamental social redesign to prevent the trajectories of harm. BEVs illustrate this. In what follows we explore the issues.

The aim of this paper, then, is to argue that it is a mistake to claim, assert or assume that BEVs are necessarily a panacea for the emissions problem. To do so would be an instance of what ecological economists refer to as ‘technocentrism’, as though simply substituting BEVs for existing internal combustion engine (ICE) vehicles was sufficient. The literature on this is, of course, vast, if one consults specialist journals or recent monographs (e.g. Chapman, 2007 ; Bailey and Wilson, 2009 ; Williamson et al. , 2018 ), but remains relatively under-explored in general political economy circles at a time of ‘Climate Emergency’, and so warrants discussion in introductory and indicative fashion, setting out, however incompletely, the range of issues at stake. To be clear, the very fact that there is a range is itself important. BEVs are technology, technologies have social contexts and social contexts include systemic features and related attitudes and behaviours. Technocentrism distracts from appropriate recognition of this. At its worse, technocentrism fails to address and so works to reproduce a counter-productive ecological modernisation: the technological focus facilitates socio-economic trends, which are part of the broader problem rather than solutions to it. In the case of BEVs, key areas to consider and points to make include:

Transport is now one of, if not, the major source of carbon emissions in the UK and in many other countries. Transport emissions stubbornly resist reduction. The UK, like many other countries, exhibits contradictory trends and policy claims regarding future carbon emissions reductions. As such, it is an error to simply assume prior emissions reduction trends will necessarily continue into the future, and the new net-zero goal highlights the short time line and urgency of the problem.

Whilst BEVs are, from an emissions point of view, a superior technology to ICE vehicles, this is less than an ordinary member of the public might think. ‘Embodied emissions’, ‘energy mix’ and ‘life cycle’ analysis all matter.

There is a difference between ‘superior technology’ and ‘superior choice’, the latter must also take account of the scale of and general trend growth in vehicle ownership and use. It is this that creates a meaningful context for what substitution can be reasonably expected to achieve.

A 1:1 substitution of BEVs for ICE vehicles and general growth in the number of vehicles potentially violates the Precautionary Principle. It creates a problem that did not need to exist, e.g. since there is net growth, it involves ‘emission reductions’ within new emissions sources and this is reckless. Inter alia , a host of fallacies and other risks inherent to the socio-economy of BEVs and resource extraction/dependence also apply.

As such, it makes more sense to resist rather than facilitate techno-political lock-in or path-dependence on private transportation and instead to coordinate any transition to BEVs with a more fundamental social redesign of public transport and transport options.

This systematic statement should be kept in mind whilst reading the following. Cumulatively, the points stated facilitate appropriate consideration of the question: What kind of solution are BEVs to what kind of problem? And we return to this in the conclusion. It is also worth bearing in mind, though it is not core to the explicit argument pursued, that an economy is a complex evolving open system and economics has not only struggled to adequately address this in general, it has particularly done so in terms of ecological issues (for relevant critique, see especially the work of Clive Spash and collected, Fullbrook and Morgan, 2019 ). 5 Since we assume limited prior knowledge on the part of the reader, we begin by briefly setting out the road to the current carbon budget problem.

The United Nations Framework Convention on Climate Change (UNFCCC) was created in 1992. Article 2 of the Convention states its goal as, the ‘stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system’ ( UNFCCC, 1992 , p. 4; Gills and Morgan, 2019 ). Emissions are cumulative because emitted CO 2 can stay in the atmosphere for well over one hundred years (other greenhouse gases [GHGs] tend to be of shorter duration). Our climate future is made now. The Intergovernmental Panel on Climate Change (IPCC) collates existent models to produce a forecast range and has typically used atmospheric CO 2 of 450 ppm as a level likely to trigger a 2°C average warming. This has translated into a ‘carbon budget’ restricting total cumulative emissions to the lower end of 3,000+ Gigatonnes of CO 2 (GtCO 2 ). In the last few years, climate scientists have begun to argue that positive feedback loops with adverse warming and other climatological and ecological effects may be underestimated in prior models (see Hansen et al. , 2017 ; Steffen et al. , 2018 ). Such concerns are one reason why Article 2 of the UNFCCC COP 21 Paris Agreement included a goal of at least trying to do better than the 2°C target—restricting warming to 1.5°C. This further restricts the available carbon budget. However, current Paris Agreement country commitments stated as NDCs look set to exceed the 3,000+ target in a matter of a few short years ( UNFCCC, 2015 ; Morgan, 2016 , 2017 ).

Since the industrial revolution began, we have already produced more than 2,000 GtCO 2 . Total annual emissions have increased rather than decreased over the period in which the problem has been recognised. The United Nations Environment Program (UNEP) publishes periodic ‘emissions gap’ reports. Its recent 10-year summary report notes that emissions grew at an average 1.6% per year from 2008 to 2017 and ‘show no signs of peaking’ ( Christensen and Olhoff, 2019 , p. 3). In 2018, the 9th Report stated that annual emissions in 2017 stood at a record of 53.5 Gigatonnes of CO 2 and equivalents (GtCO 2e ) ( UNEP, 2018 , p. xv). This compares to less than 25 GtCO 2 in 2000 and far exceeds on a global basis the level in the Kyoto Protocol benchmark year of 1990. According to the 9th Emissions Gap Report, 184 parties to the Paris Agreement had so far provided NDCs. If these NDCs are achieved, annual emissions in 2030 are projected to still be 53 GtCO 2e . However, if the current ‘implementation deficit’ continues global annual emissions could increase by about 10% to 59 GtCO 2e . This is because current emissions policy is not sufficient to offset the ‘key drivers’ of ‘economic growth and population growth’ ( Christensen and Olhoff, 2019 , p. 3). By sharp contrast, the IPCC Global Warming of 1.5 ° C report states that annual global emissions must fall by 45% from the 2017 figure by 2030 and become net zero by mid-century in order to achieve the Paris target ( IPCC, 2018 ). According to the subsequent 10th Emissions Gap Report, emissions increased yet again to 55.3 GtCO 2e in 2018 and, as a result of this adverse trend, emissions need to fall by 7.6% per year from 2020 to 2030 to achieve the IPCC goal, and this contrasts with less than 4% had reductions begun in 2010 and 15% if they are delayed until 2025 ( UNEP 2019A ). Current emissions trends mean that we will achieve an additional 500 GtCO 2 quickly and imply an average warming of 3 to 4°C over the rest of the century and into the next. We are thus on track for the ‘dangerous anthropogenic interference with the climate system’ that the COP process is intended to prevent ( UNFCCC, 1992 , p. 4). According to the 10th Emissions Gap Report, 78% of all emissions derive from the G-20 nations, and whilst many countries had recognised the need for net zero, only 5 countries of the G-20 had committed to this and none had yet submitted formal strategies. COP 25, December 2019, meanwhile, resulted in no overall progress other than on measurement and finance (for detailed analysis, see Newell and Taylor, 2020 ). As such, the situation is urgent and becoming more so.

Problems, moreover, have already begun to manifest ( UNEP 2019B , 2019B ; IPCC 2019A , 2019B ). Climate change does not respect borders, some countries may be more adversely affected sooner than others, but there is no reason to assume that cumulative effects will be localised. Moreover, there is no reason to assume that they will be manageable based on our current designs for life. In November 2019, several prominent systems and climate scientists published a survey essay in Nature highlighting nine critical climate tipping points that we are either imminently approaching or may have already exceeded ( Lenton et al. , 2018 ). In that same month, more than 11,250 scientists from 153 countries (the Alliance of World Scientists) signed a letter published in BioScience concurring that we now face a genuine existential ‘Climate Emergency’ and warning of ‘ecocide’ if ‘major transformations’ are not forthcoming ( Ripple et al. , 2019 ). We live in incredibly complex interconnected societies based on long supply chains and just in time delivery–few of us (including nations) are self-sufficient. Global human civilisation is extremely vulnerable and the carbon emission problem is only one of several conjoint problems created by our expansionary industrialised-consumption system. Appropriate and timely policy solutions are, therefore, imperative. Cambridge now has a Centre for the Study of Existential Risk and Oxford a Future of Humanity Institute (see also Servigne and Stevens, 2015 ). This is serious research, not millenarian cultishness. The Covid-19 outbreak only serves to underscore the fragility of our systems. As Michael Marmot, Professor of epidemiology has commented, the outbreak reveals not only how political decisions can make systems more vulnerable, but also how governments can, when sufficiently motivated, take immediate and radical action (Harvey, 2020). To reiterate, however, according to both the IPCC and UNEP, emissions must fall drastically. 6

Policy design and implementation are mainly national (domestic). As such, an initial focus on the UK provides a useful point of departure to contextualise what the transition to BEVs might be expected to achieve.

The UK is a Kyoto and Paris signatory. It is a member of the European Emissions Trading Scheme (ETS). The UK Climate Change Act 2008 was the world’s first long-term legally binding national framework for targeted statutory reductions in emissions. The Act required the UK to reduce its emissions by at least 80% by 2050 (below the 1990 baseline; this has been broadly in line with subsequent EU policy on the subject). 7 The Act put in place a system of five yearly ‘carbon budgets’ to keep the UK on an emissions reduction pathway to 2050. The subsequent carbon budgets have been produced with input from the Committee on Climate Change (CCC), an independent body created by the 2008 Act to advise the government. In November 2015, the CCC recommended a target of 57% below 1990 levels by the early 2030s (the fifth carbon budget). 8 Following the Paris Agreement’s new target of 1.5°C and the IPCC and UNEP reports late 2018, the CCC published the report Net Zero: The UK’s contribution to stopping global warming ( CCC, 2019 ). 9 The CCC report recognises that Paris creates additional responsibility for the UK to augment and accelerate its targets within the new bottom-up Paris NDC procedure. The CCC recommended an enhanced UK net-zero GHG emissions target (formally defined in terms of long-term and short-term GHGs) by 2050. This included emissions from aviation and shipping and with no use of strategies that offset or swap real emissions. In June 2019, Theresa May, then UK Prime Minister, committed to adopt the recommendation using secondary legislation (absorbed into the 2008 Act—but without the offset commitment). So, the UK is one of the few G-20 countries to, so far, provide a formal commitment on net zero, though as the UNEP notes, a commitment is not itself necessarily indicative of a realisable strategy. The CCC responded to the government announcement:

This is just the first step. The target must now be reinforced by credible UK policies, across government, inspiring a strong response from business, industry and society as a whole. The government has not yet moved formally to include international aviation and shipping within the target , but they have acknowledged that these sectors must be part of the whole economy strategy for net zero. We will assist by providing further analysis of how emissions reductions can be delivered in these sectors through domestic and international frameworks. 10

The development of policy is currently in flux during the Covid-19 lockdown and whilst Brexit reaches some kind of resolution. As noted in the Introduction section, however, May’s replacement, Boris Johnson has signalled his government’s commitment to achieving its statutory commitments. However, this has been met with some scepticism, not least because it has not been clear what new powers administrative bodies would have and over and above this many of the Cabinet are from the far right of the Conservative Party, and are on record as climate change sceptics or have a voting record of opposing environmentally focussed investment, taxes, subsidies and prohibitions (including the new Environment Secretary, George Eustice, formerly of UKIP). The policy may and hopefully will change, becoming more concrete, but it is still instructive to assess context and general trends.

The UK has one of the best records in the world on reducing emissions. However, given full context, this is not necessarily a cause for congratulation or confidence. It would be a mistake to think that emissions reduction exhibits a definite rate that can be projected from the past into the future. 11 This applies both nationally and globally. Some sources of relative reduction that are local or national have different significance on a global basis (they are partial transfers) and overall the closer one approaches net zero the more resistant or difficult it is likely to become to achieve reductions. The CCC has already begun to signal that the UK is now failing to meet its existent budgets. This follows periods of successive emissions reductions. According to the CCC, the UK has reduced its GHG emissions by approximately one-third since 1990. ‘Per capita emissions are now close to the global average at 7–8 tCO 2 e/person, having been over 50% above in 2008’ ( CCC, 2019 , p. 46). Other analyses are even more positive. According to Carbon Brief, emissions have fallen in seven consecutive years from 2013 to 2019 and by 40% compared with the 1990 benchmark. Carbon Brief claim that since 2010 the UK has the fastest rate of emissions reduction of any major economy. However, it concurs with the CCC that future likely reductions are less than the UK’s carbon budgets and that the new net-zero commitment requires: amounting to only an additional 10% reduction over the next decade to 2030. 12

Moreover, all analyses agree that the reduction has mainly been achieved by reducing coal output for use in electricity generation (switching to natural gas) and by relative deindustrialisation as the UK economy has continued to grow—manufacturing is a smaller part of a larger service-based economy. 13 And , the data are based on a production focussed accounting system. The accounting system does not include all emissions sources. It does not include those that the UK ‘imports’ based on consumption. UK consumption-based emissions per year are estimated to be about 70% greater than the production measure (for different methods, see DECC, 2015 ). 14 If consumption is included, the main estimates for falling emissions change to around a 10% reduction since 1990. Moreover, much of this has been achieved by relatively invisible historic transitions as the economy has evolved in lock-step with globalisation. That is, reductions have been ones that did not require the population to confront behaviours as they have developed. No onerous interventions have been imposed, as yet . 15 However, it does not follow that this can continue, since future reductions are likely to be more challenging. The UK cannot deindustrialise again (nor can the global economy, as is, simply deindustrialise in aggregate if final consumption remains the primary goal), and the UK has already mainly switched from coal energy production. Emissions from electricity generation may fall but it also matters what the electricity is being used to power. In any case, future emissions reductions, in general, require more effective changes in other sectors, and this necessarily seems to require everyone to question their socio-economic practices. Transport is a key issue.

As a ‘satellite’ of its National Accounts, the UK Office for National Statistics (ONS) publishes Environmental Accounts and these data are used to measure progress. Much of the data refer to the prior year or earlier. In 2017, UK GHG emissions were reported to be 566 million tonnes CO 2 e (2% less than 2016 and, as already noted about one-third of the 1990 level; ONS, 2019 ). The headline accounts break this down into four categories (for which further subdivisions are produced by various sources) and we can usefully contrast 1990 and recent data ( ONS, 2019 , p. 4):

The Environmental Accounts’ figures indicate some shifting in the relative sources of emissions over the last 30 years. As we have intimated, electricity generation and manufacturing have experienced reduced emissions, though they are far from zero; household and transport, meanwhile, have remained stubbornly high. Moreover, the accounts are also slightly misleading for the uninitiated, since transport refers to the industry and not all transport. Domestic car ownership and use are part of the household sector, and it is the continued dependence on car ownership that provides, along with heating and insulation issues, one of the major sources of the persistently high level of household emissions. The UK Department for Business, Energy and Industrial Strategy (DBEIS) provides differently organised statistics and attributes cars to its transport category and uses a subsequent residential category rather than household category. The Department’s statistical release in 2018 thus attributes a higher 140 MtCO 2 e to transport for 2016, whilst the residential category is a correspondingly lower figure of approximately 106 MtCO 2 e. The 140 MtCO 2 e is just slightly less than the equivalent figure for 1990, although transport achieved a peak of about 156 MtCO 2 e in 2005 ( DBEIS, 2018 , pp. 8–9). As of 2016, transport becomes the largest source of emissions based on DBEIS data (exceeding energy supply) whilst households become the largest in the Environmental Accounts. In any case, looking across both sets of accounts, the important point here is that since 1990 transport as a source of emissions has remained stubbornly high. Transport emissions have been rising as an industrial sector in the Environmental Accounts or relatively consistent and recently rising in its total contribution in the DBEIS data. The CCC Net Zero report draws particular attention to this. Drawing on the DBEIS data, it states that ‘Transport is now the largest source of UK GHG emissions (23% of the total) and saw emissions rise from 2013 to 2017’ ( CCC, 2019 , p. 48). More generally, the report states that despite some progress in terms of the UK carbon budgets, ‘policy success and progress in reducing emissions has been far from universal’ ( CCC, 2019 , p. 48). The report recommends ( CCC, 2019 , pp. 23–6, 34):

A fourfold increase by 2050 in low carbon (renewables) electricity

Developing energy storage (to enhance the use of renewables such as wind)

Energy-efficient buildings and a shift from gas central heating and cooking

Halting the accumulation of biodegradable waste in landfills

Developing carbon capture technology

Reducing agricultural emissions (mainly dairy but also fertiliser use)

Encouraging low or no meat diets

Land management to increase carbon retention/absorption

Rapid transition to electric vehicles and public transport

As we noted in the Introduction section, the UK Department for Transport Road To Zero document stated a goal of ending the sale of conventional diesel- and petrol-powered ICE vehicles by 2040. The CCC suggested improving on this:

Electric vehicles. By 2035 at the latest all new cars and vans should be electric (or use a low-carbon alternative such as hydrogen). If possible, an earlier switchover (e.g. 2030) would be desirable, reducing costs for motorists and improving air quality. This could help position the UK to take advantage of shifts in global markets. The Government must continue to support strengthening of the charging infrastructure, including for drivers without access to off-street parking. ( CCC, 2019 , p. 34)

The UK government’s response to these and other similar suggestions has been to bring the target date forward to 2035 and to propose that the prohibition will also apply to hybrids. However, the whole is set to go out to consultation and no detail has so far (early 2020) been forthcoming. In its 11 March 2020 Budget, the government also committed £1 billion to ‘green transport solutions’, including £500 million to support the rollout of the electric vehicle charging infrastructure, whilst extending the current grant/subsidy scheme for new electric vehicles (albeit at a reduced rate of £3000 from £3500 per new registration). It has also signalled that it may tighten the timeline for sales prohibition further to 2030. 16 As a policy, much of this is, ostensibly at least, positive, but there is a range of issues that need to be considered regarding what is being achieved. The context of transition matters and this may transcend the specifics of current policy.

3.1 BEV transition: life cycles?

The CCC is confident that a transition to electric vehicles can be a constructive contribution to achieving net-zero emissions by mid-century. However, the point is not unequivocal. The previously quoted CCC communique following the UK government’s commitment to implement Net Zero uses the phrase ‘credible UK policies, across government, inspiring a strong response from business, industry and society as a whole’, and the CCC report places an emphasis on BEVs and a transition to public transport. The relative dependence between these two matters (and see Conclusion). BEVs are potentially (almost) zero emissions in use. But they are not zero emissions in practice. Given this, then the substitution of BEVs for current carbon-powered ICEs is potentially problematic, depending on trends in ownership of and use of powered vehicles (private transportation). These points will become clearer as we proceed.

BEVs are not zero emission in context and based on the life cycle. This is for two basic reasons. First, a BEV is a powered vehicle and so the source of power can be from carbon-based energy supply sources (and this varies with the ‘energy mix’ of electricity production in different countries; IEA, 2019A , p. 8). Second, each new vehicle is a material product. Each vehicle is made of metals, plastics, rubber and so forth. Just the cabling in a car can be 60 kg of metals. All the materials must be mined and processed, or synthesised, the parts must be manufactured, transported and assembled, transported again for sale and then delivered. For example, according to the SMMT in 2016, only 12% of cars sold in the UK were built in the UK and 80% of those built in the UK were exported in that year. Some components (such as a steering column) enter and exit the UK multiple times whilst being built and modified and before final assembly. Vehicle manufacture is a global business in terms of procuring materials and a mainly regional (in the international sense) business in terms of component manufacture for assembly and final sales. Power is used throughout this process and many miles are travelled. Moreover, each vehicle must be maintained and serviced thereafter, which compounds this utilisation of resources. BEVs are a subcategory of vehicles and production locations are currently more concentrated than for vehicles in general (Tesla being the extreme). 17 In any case, producing a BEV is an economic activity and it is not environmentally costless. As Georgescu-Roegen (1971) noted long ago and ecologically minded economists continue to highlight (see Spash, 2017 ; Holt et al. , 2009 ), production cannot evade thermodynamic consequences. In terms of BEVs, the primary focus of analysis in this second sense of manufacturing as a source of contributory emissions has been the carbon emissions resulting from battery production. Based on current technology, batteries are heavy (a significant proportion of the weight of the final vehicle) and energy intensive to produce.

Comparative estimates regarding the relative life cycle emissions of BEVs with equivalent fossil fuel-powered vehicles are not new. 18 Over the last decade, the number of life cycle studies has steadily risen as the interest in and uptake of BEVs have increased. Clearly, there is great scope for variation in findings, since the energy mix for electricity supply varies by country and the assumptions applied to manufacturing can vary between studies. At the same time, the general trend over the last decade has been for the energy mix in many countries to include more renewables and for manufacturing to become more energy efficient. This is partly reflected in metrics based on emissions per $GDP, which in conjunction with relative expansion in service sectors are used to establish ‘relative decoupling’. So, given that both the energy mix of power production and the emissions derived from production can improve, then one might expect a general trend of improved emissions claims for BEVs in recent years and this seems to be the case.

For example, if we go back to 2010, the UK Royal Academy of Engineering found that technology would likely favour PHEVs over BEVs in the near future because the current energy mix and state of battery technology indicated that emissions deriving from charging were typically higher for BEVs than an average ordinary car’s fuel consumption—providing a reason to persist with ICE vehicles or, more responsibly, choose hybrids over pure electric ( Royal Academy of Engineering, 2010 ). Using data up to 2013, but drawing on the previous decade, Holtsmark and Skonhoft (2014) come to similar conclusions based on the most advanced BEV market—Norway. Focussing mainly on energy mix (with acknowledgement that a full life cycle needs to be assessed) they are deeply sceptical that BEVs are a significant net reduction in carbon emissions ( Holtsmark and Skonhoft, 2014 , pp. 161, 164). Neither the Academy nor Holtsmark and Skonhoft are merely sceptical. The overall point of the latter was that more needed to be done to accelerate the use of low or no carbon renewables for power infrastructure (a point the CCC continues to make). This, of course, has happened in many places, including the UK. That is, acceleration of the use of renewables, though it is by no means the case government can take direct credit for this in the UK (and there is also evidence on a global level that a transition to clean energy from fossil fuel forms is much slower than some data sources indicate; see Smil, 2017A , 2017B ). 19 In terms of BEVs, however, recent analyses are considerably more optimistic regarding emissions potential per BEV (e.g. Hoekstra, 2019 ; Regett et al. , 2019 ). Research by Staffell et al. (2019) at Imperial for the power corporation, Drax, provides some interesting insights and contemporary metrics.

Staffell et al. split BEVs into three categories based on conjoint battery and vehicle size: a 30–45 kWh battery car, equivalent to a mid-range or standard car; a heavier, longer-range, 90–100 kWh battery car, equivalent to a luxury or SUV model; and a 30–40 kWh battery light van. They observe that a 40-litre tank of petrol releases 90–100 kgCO 2 when burnt and the ‘embodied’ emissions represented by the manufacture of a standard lithium-ion battery are estimated at 75–125 kgCO 2 per kWh. They infer that every kWh of power embodied in the manufacture of a battery is, therefore, approximately equivalent to using a full tank of petrol. For example, a 30 kWh battery embodies thirty 40-litre petrol tank’s worth of emissions. The BEV’s are also a source of emissions based on the energy mix used to charge the battery for use. The in-use emissions for the BEV are a consequence of the energy consumed per km and this depends on the weight of car and efficiency of the battery. 20 They estimate 33 gCO 2 per km for standard BEVs, 44–54 gCO 2 for luxury and SUVs and 40 gCO 2 for vans. In all cases, this is significantly less than an equivalent fossil-fuel vehicle.

The insight that the estimates and comparisons are leading towards is that the battery embodies an ‘upfront carbon cost’ which can be gradually ‘repaid’ by the saving on emissions represented by driving a BEV compared with driving an equivalent fossil fuel-powered vehicle. That is, the environmental value of opting for BEVs increases over time. Moreover, if the energy mix is gradually becoming less carbon based, this effect is likely to improve further. Based on these considerations, Staffell et al. estimate that it may take 2–4 years to repay the embodied emissions in the battery for a standard BEV and 5 to 6 for the luxury or SUV models. Fundamentally, assuming 15 years to be typical for the on-the-road life expectancy of a vehicle, they find lifetime emissions for each BEV category are lower than equivalent fossil-fuel vehicles.

Still, the implication is that BEVs are not zero emission. Moreover, the degree to which this is so is likely to be significantly greater than a focus on the battery alone indicates. Romare and Dahlöff (2017) , assess the life-cycle of battery production (not use), and in regard of the stages of battery production find that the manufacturing stages account for about 50% of the emissions and the mining and processing stages about the same. They infer that there is significant scope for further emissions reductions as manufacturing processes improve and the Drax study seems to confirm this. However, whilst the battery may be the major component, as we have already noted, vehicle manufacture is a major process in terms of all components and in terms of distance travelled in production and distribution. It is also worth noting that the weight of batteries creates strong incentives to opt for lighter materials for other parts of the vehicle. Most current vehicles are steel based. An aluminium vehicle is lighter, but the production of aluminium is more carbon intensive than steel, so there are also further hidden trade-offs that the positive narrative for BEVs must consider. 21

The general point worth emphasising here is that there is basic uncertainty built into the complex evolving process of transition and change. There is a basic ontology issue here familiar in economic critique: there is no simple way to model the changes with confidence, and in broader context confidence in modelling may itself be a problem here when translated into policy, since it invites complacency. 22 That said, the likely direction of travel is towards further improvements in the energy mix and improvements in battery technology. Both these may be incremental or transformational depending on future technologies (fusion for energy mix and organics and solid-state technologies for batteries perhaps). 23 But one must still consider time frames and ultimate context. 24 The context is a carbon budget and the need for radical reductions in emissions by 2030 and net zero by mid-century. Consider: if just the battery of a car requires four years to be paid back then there is no significant difference in the contribution to emissions from the vehicle into the mid 2020s. For larger vehicles, this becomes the later 2020s, and each year of delay in transition for the individual owner is another year closer to 2030. Since transport is (stubbornly) the major source of emissions in the UK and a major source in the world, this is not irrelevant. BEVs can readily be a successful failure in Paris terms. This brings us to the issue of trends in vehicle ownership and substitutions. This also matters for what we mean by transition.

3.2 Substitutions and transformations: successful failure?

There are many ways to consider the problem of transition. Consider the ‘Precautionary Principle’. This is Principle 15 of the 1992 Rio Declaration: ‘In order to protect the environment, the precautionary principle shall be widely applied by the States [UN members] according to their capabilities. Where there are threats of serious or irreversible damage, lack of full scientific certainty shall not be used as a reason for postponing cost-effective measures to prevent environmental degradation’ (UNCED). Assuming we can simply depend on unrealised technology potentially violates the Principle. Why is this so? If BEVs are a source of net emissions, then each new vehicle continues to contribute to overall emissions. The current number of vehicles to be replaced, therefore, is a serious consideration, as is any growth trend. Here, social redesign rather than merely adopting new technology is surely more in accordance with the Precautionary Principle. BEVs may be sources of lower emissions than fossil fuel-powered vehicles, but it does not follow that we are constrained to choose between just these two options or that it makes sense to do so in aggregate, given the objective of radical and rapid reduction in emissions. If time is short and numbers of vehicles are large and growing then the implication is that substitution of BEVs should (from a precautionary point of view) occur in a context that is oppositional to this growing trend. That is, the goal should be one of reducing private car ownership and use, and increasing the availability, pervasiveness and use of public transport (and alternatives to private vehicle ownership). This is an issue compounded by the finding that there is an upfront carbon cost from BEVs. Some consideration of current vehicle numbers and trends in the UK and globally serve to reinforce the point.

The UK Department for Transport publishes annual statistics for vehicle licensing. According to the 2019 statistical release for 2018 data, there were 38.2 million licensed vehicles in Britain and 39.4 million including Northern Ireland ( Department for Transport, 2019 ). Vehicles are categorised into cars, light goods vehicles, heavy goods vehicles, motorcycles and buses and coaches. Cars comprised 31.5 million of the total (82%) and the total represented a 1.2% increase in the year 2017. There is, furthermore, a long-term year-on-year trend increase in vehicles since World War II and over the last 20 years that growth (the net change as new vehicles are licensed and old vehicles taken off the road) has averaged 630,000 vehicles per year ( Department for Transport, 2019 , p. 7). This is partly accounted for not only by population growth, and business growth, but also by an increase in the number of vehicles per household. According to the statistical release, 2.9 million new vehicles were registered in 2018, and though this was about 5% fewer than 2017 the figure remained broadly consistent with long-term trends in numbers and still represented growth (contributing to the stated 1.2% increase). 25 Of the total new registrations in 2018, 2.3 million were cars and 360,000 were light goods vehicles. Around 2 million has been typical for cars.

The point to take from these metrics is that numbers are large and context matters. Cars represent 31.5 million emission sources and there are 39.4 million vehicles in the UK. Replacing these 1:1 reproduces an emissions problem. Replacing them in conjunction with an ownership growth trend exacerbates the emissions problem that then has to be resolved. If around 2 million new cars are registered per year then the point at which the BEVs amongst these new registrations can be assumed to begin payback for embodied emissions prior to the point at which they become net sources of reduced (and not zero ) emissions is staggered over future years based on the rate of switching. There are then also net new vehicles. Given there are 31.5 million cars to be replaced over time (plus net growth), there is a high likelihood of significant transport emissions up to and beyond 2030. The problem, of course, is implicit in the Department for Transport policy commitment to end sales of petrol and diesel vehicles by 2035 and ensure all vehicles are zero-emission in use by 2050. Knowingly committing to this ingrained emission problem, given we have already recognised the urgency and challenge of the carbon budget and the ‘stubbornness’ of transport emissions, is not prudent, if alternatives exist . It is producing a problem that need not exist purely because enabling car ownership and use is a line of least resistance in policy terms (it requires the least change in behaviour and thus provokes limited opposition). It is also worth noting that the UK, like most countries, has an ‘integrated’ transport policy. However, the phrasing disguises the relative levels of investment between different modes of transport. Austerity politics may have resulted in declining road quality in the UK but, in general terms, the UK is still committed to heavy investment in and expansion of its road system. 26 This infrastructure investment not only seems ‘economically rational’, but it is also a matter of relative emphasis and ‘lock-in’. The future policy is predicated on the dominance of road use and thus vehicle use.

The crux of the matter here is how we view political expedience. Surely this hinges on the consequences of policy failure. That is, the failure to implement an effective policy given the genuine problem expressed in the goal of 1.5 or 2°C. ‘Alternatives’ may seem unrealistic, but this is a matter of will and policy—of rational social design rather than impossibility. The IPCC and other sources suggest that achieving the Paris goals requires mobilisation of a kind not previously seen outside of wartime. Policy can pivot on this quite quickly, even if perhaps this can seem unlikely in 2020. Climate events may make this necessary and popular pressure and opinion may be transformed. This is currently uncertain. Positions on this may yet move quite quickly.

Lock-in also implies an underlying sociological issue. This is important to consider regarding simply opting for substitution without greater emphasis on reduction. Even if substitution occurs smoothly, it places greater pressure on areas of reduction over which we have less control as societies and involves an orientation that has further potential policy consequences that cannot be readily quantified and which increase the overall uncertainty regarding NDCs. As any modern historian, urban geographer or sociologist will attest, car ownership has been imbricate with the development and design—the configuration—of modern societies, and it has been deeply integrated into identity. Cars are social technologies and philosophers also have much to say about this sociality in general (e.g. Faulkner and Runde, 2013 ; Lawson, 2017 ). Cars are more than merely convenient; they are sources of autonomy and status (e.g. John Urry explored the sociology of ‘automobility’; see, Dennis and Urry, 2009 ). As such, the more that environmental and transport policy validate the car, then the more that the car is normalised through socialisation for the citizen, perhaps leading to citizens being more prepared to countenance locked-in harms (congestion, etc.) prior to change, in turn, making it less likely (sub)urban spaces are redesigned in ways predicated on the absence of (or severe limits to) private transport. The trend in many countries over the car era has been that building roads leads to more car use, which leads to congestion, which leads to more roads (especially in concentrated zones around [sub]urban spaces).

According to the UK Ordnance Survey, Britain has increased its total road surface by 132 square miles over the decade since 2010 (a 9% increase). According to the UK Department for Transport, vehicle traffic increased by 0.8% in 2019 (September to September) to 330.1 billion miles travelled and car travel, as a subset, increased to 258 billion miles (a 1.5% increase). 27 The 11 March 2020 Budget seems to confirm the trend. Whilst it commits around £1 billion to ‘green transport solutions’, this is in the context of a £27 billion announced investment in roads, including upgrading and a proposed 4,000 miles of new road. As the Green Party MP, Caroline Lucas, noted there is a basic disconnect here, since this seems set to increase the UK’s dependence on private transport, when it makes more sense to begin to curtail that dependence, given how significant the UK’s transport emissions are. 28 So, within the various tensions in policy, there seems to be a tendency to facilitate techno-political lock-in or path-dependence on private transportation. As Mattioli et al. (2020) argue, the multiple strands of policy and practice that maintain car dependence contribute to ‘carbon lock-in’. The systemic consequences matter both for the perpetuation of fossil fuel vehicle use in the short term and, given they are not net zero for emissions, powered vehicles in the longer term. Not only does this matter in the UK, but it also matters globally. All the issues stated are reproduced globally. Moreover, in some ways, they are compounded for countries where widespread car ownership is relatively new.

3.3 The fallacy of composition, problems that need not exist and resource risk

Estimates vary for the global total number of vehicles. According to Wards Intelligence, the global total was 1.32 billion in 2016 ( Petit, 2017 ). Extrapolated estimations imply that the total likely increased to more than 1.5 billion in 2019. In 1976, the figure was 342 million and in 1996, 670 million, so the trend implies an approximate doubling every 20 years, which if it continued would imply a figure approaching 3 billion by end of the 2030s. Clearly, it is problematic to simply extrapolate a linear trend, but it is not unreasonable to assume a general trend of growth. Observed experience is that many ‘developed’ country middle-class households have accommodated more than one car per household. This is classically the case in the USA. In 2017, the USA, with a population of 325.7 million in that year, reported a total of 272.5 million registered vehicles compared with 193 million in 1990 ( Statista, 2019A ). In any case, the world population is still growing, incomes are growing and many countries are far from a position of one car per household. China with a population of 1.3 billion overtook the USA in the total number of registered vehicles around 2016 to 2017, with 300.3 million registered vehicles in March of 2017 (Zheng, 2017). Growth is rapid and the China Traffic Bureau of the Ministry of Public Security reported a total of 325 million registered vehicles, December 2018, an increase of 15.56 million in the year ( China Daily , 2018 ). The People’s Republic is now the world’s largest car market and the number of registered cars increased to 240 million in 2018 ( Statista, 2019B ). India too has rapidly growing car ownership and on a lesser scale this is replicated across the developing world.

For our purposes, two well-known concepts and a further resource dependence risk seem to apply here. First, there is patently a ‘fallacy of composition’ issue. That is, the assumption that many can do what few previously did without changing the conditions or producing different (adverse) consequences than arose when only a few adopted that behaviour or activity. Those consequences are climatological and ecological. It remains the case that we are socialised to desire and appreciate cars and it remains a fact that private transport can be extremely convenient. It can also, given the commentary above, appear hypocritical to be suggesting shifting to a far greater reliance on public transport, since this implicitly involves denying to developing country citizens a facet of modernity enjoyed previously by developed country citizens. But this is a distraction from the underlying collective interest in reduced car ownership and use. It denies the basic premise that a Precautionary Principle applies to all and that societies that are not yet car dependent have the opportunity to avoid a problem, rather than have to manage it via either moving straight to private transport BEVs or a transition from fossil fuel-powered ICEs to BEVs with all that entails in terms of ingrained emissions. Policy may be mainly domestic, but climate change is global and aggregate effects do not respect borders, which brings us to a second concept or risk that may be exacerbated.

Second, a ‘quasi-Jevons’ effect’ may apply. Growth of vehicle use is a problem of resource use and this is a thermodynamic and emissions problem. However, it is, as we have noted, also the case that battery technology and energy mix for BEVs are improving. So, this may involve significant declines in relative cost, which in turn may create a tendency for BEV ownership to accelerate which could exacerbate net growth in numbers of vehicles. Net growth could ironically be to the detriment of emissions savings. Whether this is so, depends, in part, on what kind of overall transport policy countries adopt and whether consumers, corporations and markets are allowed to be the arbiter of which area of transport dominates. It also depends, in part, on what materials are required for future batteries. Current technology implies massive increases in costs based on securing sources of lithium and cobalt as battery demand rises. So even if a Jevons’ effect is avoided, a different issue may apply. Resource procurement is a Precautionary Principle issue since effective BEVs at the kind of numbers necessary to substitute for all vehicles seem to require technological transformation—without it, multiple problems apply whilst emissions remain ingrained.

For example, when the UK CCC announced its 2035 recommendation to accelerate the BEV transition, members of the Security of Supply of Mineral Resources (SSMR) project wrote a research note to the CCC (Webster, 2019). They pointed out that the current total European demand for cobalt is 19,800 tonnes and that producing the batteries to replace 2.3 million cars in the UK (in accordance with contemporary statistics for new registrations) would require 15,600 tonnes. The UK would also need 20,000 tonnes of lithium, which is 45% of the current total European demand. If we replicate this ramping up of demand across Europe and the globe for vehicles, recognising that there are other growing demands for the minerals and metals (including batteries for other purposes) then it seems unlikely that supply can respond, unless dependence on lithium and cobalt (and other constituents) falls sharply as technology changes. Clearly, the problem is also contingent on the uptake of BEVs. Over recent years, there has, in fact, been an oversupply of the main materials for battery production because several of the main mining corporations anticipated that battery demand would take off faster than it actually has. For example, global prices of cobalt, nickel and lithium carbonate have increased significantly over the last decade but have fallen in 2018 to the end of 2019. However, industry analysis indicates that current annual global production is the equivalent of about 10 million standard BEVs based on current technology, and as the previous statistics on global vehicle numbers (see also next section) indicate, this is far less than transition via substitution would seem to require in the next decade. 29

Shortages and price rises, therefore, are if not inevitable, at least likely. Currently, about 60% of the cost of a BEV is the battery and 80% of that 60% (about 50% of the vehicle) is the cost of battery materials. It is, therefore, important to achieve secure supply and stable costs. The further context here is the issue of UK domestic battery capacity. In 2013, the government created the Advanced Propulsion Centre (APC) with a 10 year £500 million investment commitment matched by industry. The APC’s remit is to address supply chain issues for electric vehicles. Not unexpectedly, the APC quickly identified lack of domestic battery production capacity as a major impediment. In response in 2016 another government initiative, Innovate UK set up the Faraday Battery Challenge to encourage domestic capacity and innovation. The Battery Industrialisation Centre was then set up in Coventry, to attract manufacturers in the supply chain for BEVs to locate there, focussed around a centre of research excellence. However, the APC has no control over the global supply and prices of battery materials, the investment and location decisions of battery manufacturers or the necessary infrastructure for BEVs to be a feasible technology. 30 For example, according to the APC, if domestic BEV demand were 500,00 per year by 2025, then the UK would need three ‘gigafactories’. Battery manufacture is currently dominated by LG Chem and Samsung in South Korea, CATL in China and Panasonic in Japan. None of these have current plans to build a gigafactory in the UK. In any case, there is a further problem here which raises a whole set of environmental and ethical issues explored in ecological circles under the general heading ‘extractivism’ (see, e.g. Dunlap, 2019 ). As time goes by, the UK and the world may become dependent on high price supplies of materials drawn from unstable or hostile regimes (the Democratic Republic of Congo, etc.), which is a risk in many ways (and a likely source of Dutch disease—the ‘resource curse’—for unstable regimes). So, not placing a relative emphasis on substituting BEVs for ICEs and not endorsing the current vehicle growth trend (which is different as a suggestion than rejecting BEVs entirely) avoid multiple problems and risks.

It is also worth noting that simple market decisions can have a further collective adverse consequence based on individual consumer preference and reasoning, which may also affect BEVs in the short term. Many current BEVs have smaller or low efficiency batteries and thus short ranges. These favour urban use for short journeys, but most people own cars with a view also to range further afield. As such, it seems likely that until the technology is all long range (and the charging infrastructure is pervasive) many consumers, if the choice exists and income allows, will own BEVs as an additional vehicle, not a replacement vehicle. 31 This may be a short-term issue, given the regulatory changes focussed from 2030 to 2040 in many countries. But, again, from a Paris point of view, taking the IPCC 1.5°C and UNEP Emissions Gap reports into consideration, this matters. This brings us to a final issue. What is the actual take-up of BEVs (and ULEVs)? How rapid is the transition? In the Introduction section, I suggested that the UK had reached a tipping point and that this mirrored a general trend globally. This, however, needs context.

3.4 How many electric vehicles?

The data emerging in recent years and stated in the Introduction section are a step-change, but as a possible tipping point it begins from a low base and BEVs (the least emitting of the low emission vehicles) are a subset, albeit a rapidly expanding one, of ULEVs. According to the UK Department for Transport statistical release for 2018, there were 200,000 ULEVs registered in total, of which 63,992 ULEVs were newly registered in that year ( Department for Transport, 2019 , p. 4). 93% of the total registrations were cars and the total constitutes a 39% increase on the year 2017 total and a 20% increase in the rate of registration—there were just 9,500 ULEVs at the beginning of 2010 (so, about 20 times greater in a decade). However, the 2018 data mean that ULEVs accounted for just 0.5% of all licensed vehicles and were still only 2.1% of all new registrations in that year. Preliminary data available early 2020 indicate continued growth with almost 38,000 new BEV registrations in 2019, a 144% year-on-year increase. As a recent UK House of Commons Briefing Paper notes, however, the government prefers to emphasise the percentage changes in take-up rather than the percentages of the absolute numbers or the absolute numbers themselves ( Hirst, 2019 ). The International Energy Agency (IEA) places the UK in its leading countries list by ULEV and BEV market share (measured by the percentage of total annual registration): Norway dominates, followed by Iceland, Sweden, the Netherlands and then a significant drop-off to a trailing group including China, the USA, Germany, the UK, Japan, France, Canada and South Korea. However, the market share in this trailing group is less than 5% in every case (see appended Figure 1 ). China, given its size (and because of the urgency of its urban air quality problems and its capacity for authoritarian implementation), dominates the raw numbers in terms of total ULEVs and BEVs. All this notwithstanding, the IEA confirms the general point that up-take is accelerating, but the base is low and so achieving total ULEV or BEV coverage is some way off:

The global electric car fleet exceeded 5.1 million in 2018, up by 2 million since 2017, almost doubling the unprecedented amount of new registrations in 2017. The People’s Republic of China… remained the world’s largest electric car market with nearly 1.1 million electric cars sold in 2018 and, with 2.3 million units, it accounted for almost half of the global electric car stock. Europe followed with 1.2 million electric cars and the United States with 1.1 million on the road by the end of 2018 and market growth of 385000 and 361000 electric cars from the previous year. Norway remained the global leader in terms of electric car market share at 46% of its new electric car sales in 2018, more than double the second-largest market share in Iceland at 17% and six-times higher than the third-highest Sweden at 8%. In 2018, electric buses continued to witness dynamic developments, with more than 460000 vehicles on the world’s road, almost 100000 more than in 2017…In freight transport, electric vehicles (EVs) were mostly deployed as light-commercial vehicles (LCVs), which reached 250000 units in 2018, up 80000 from 2017. Medium truck sales were in the range of 1000–2000 in 2018, mostly concentrated in China. ( IEA, 2019A , p. 9)

Over the next few years, it seems likely we will see rapid changes in these metrics. There is a great deal of discussion in policy analysis regarding bottlenecks and impediments and these, of course, are also important (consumer uncertainty, ‘range anxiety’, availability of sufficient infrastructure for charging and so on). 32 However, as everything argued so far indicates regarding transition and trends, underlying the whole is the conditionality of success and the potential for failure, involving avoidable ingrained emission and risks. There is a basic difference between a superior technology and a superior choice since the latter is a socio-economic matter of context: of rates of change, scales and substitutions. Ultimately, this creates deep concerns in terms of achieving the Paris goals. The IEA explores two forecast scenarios for the uptake of ULEVs. Both involve a projection of annual ULEV sales and total stock to 2030 ( IEA, 2019A ). First a ‘New Policies’ Scenario. This takes the current policy commitments of individual countries and extrapolates. By 2030, the scenario projects global ULEV sales at 23 million in that year and a total stock of 130 million. This is considerably less than 30% of all vehicles now and in 2030. Second, the EV30@30 Scenario. This assumes an accelerated commitment that adopts the @30 goals (notably 30% annual sales share for BEVs by 2030; IEA, 2019A , pp. 29–30). By 2030, the scenario projects global ULEV sales at 43 million in that year and a total stock of 250 million. Again, this is less than 30% of all vehicles now and in 2030.

The figures, of course, are highly conditional, but the point is clear, even the best-case scenario currently being anticipated has ULEVs and BEVs as a minority of all vehicles in 2030—and 2030 is a key year for achieving Paris, according to the October 2018 IPCC 1.5°C report. Moreover, it is notable that the projections assume continuous growth in the number of vehicles (and so continuous growth in ICE vehicles) and the major areas of numerical growth in BEVs continue to be China, so some significant part of the anticipated total will be new ingrained emissions that arguably did not need to exist. 33 Again, this is highly conditional but it at least creates questions regarding what is being ‘saved’ when the IEA claims that the New Policies Scenario results in 2.5 million barrels a day less demand for oil in 2030 and the EV30@30 Scenario 4.3 million barrels a day ( IEA, 2019A , p. 7). 34 Less of more is not a saving in an objective sense, if this is a preventable future, and it is not a rational way to set about ‘saving’ the planet. It remains the case, of course, that this is better than nothing, but it is deeply questionable whether in policy terms any of this is the ‘best that can be done’. As stated in the Introduction section, technocentrism distracts from appropriate recognition of this. At its worse, technocentrism fails to address and so works to reproduce a counter-productive ecological modernisation: the technological focus facilitates socio-economic trends, which are part of the broader problem rather than solutions to it. The important inference is that there are multiple reasons to think that greater emphasis on social redesign and less private transport avoids successful failure and is more in accordance with the Precautionary Principle.

I ended the introduction to this essay by stating that we would be exploring the foregrounding question: What kind of solution are BEVs to what kind of problem? It should be clearer now what was meant by this. Ultimately, the balance between private and public transport matters if the Paris goals are to be achieved. Equally clearly, this is not news to the UK CCC or to any serious analyst of electric vehicles and the transport issue for our climatological and ecological future (again, e.g. Chapman, 2007 ; Bailey and Wilson, 2009 ; Williamson et al. , 2018 ; Mattioli et al. , 2020 ). At the same time, the context and issues are not widely understood and the problems are often understated, at least in so far as, discursively, most weight is placed on stating progress in achieving a transition to ULEVs and BEVs. This is technocentric. Despite its general concerns and careful critical stance, the CCC is also partly guilty of this. For example, Ewa Kmietowicz, Transport Team Leader of the CCC Secretariat, refers to the UK Road to Zero strategy as a ‘lost opportunity’, and the CCC identifies a number of shortfalls in the strategy. 35 However, the general thrust of the CCC position is to focus on a rapid transition to BEVs and to overcoming bottlenecks. 36 Broader feasibility is subsumed under general assumptions about continued economic expansion and expansion of the transport system. So, there is more of a situation of complementarity (with caveats) between public and private transport, and the whole becomes an exercise in types of investment within expansionary trends, rather than a more radical recognition of the fundamental problems that we ought to think about avoiding. It is also worth noting that many of the major advocates of BEVs are industry organisations. The UK Society of Motor Manufacturers and Traders, for example, are not unconcerned but they are not impartial either; they have a vested interest in the vehicle industry and its growth. For industry, ULEVs and BEVs are an opportunity before they are a solution to a problem. There are, however, recognitions that a rethink is required. These range from direct activism, such as ‘Rocks in the Gearbox’ (along the lines of Extinction Rebellion), to analysis from establishment think tanks, such as the World Economic Forum 37 , and statements from government oversight committees. For example, the UK Commons Science and Technology Committee (CSTC) not only endorses the CCC 2035 accelerated BEV target but also states more explicitly:

In the long-term, widespread personal vehicle ownership does not appear to be compatible with significant decarbonisation. The Government should not aim to achieve emissions reductions simply by replacing existing vehicles with lower-emissions versions. Alongside the Government’s existing targets and policies, it must develop a strategy to stimulate a low-emissions transport system, with the metrics and targets to match. This should aim to reduce the number of vehicles required, for example by: promoting and improving public transport; reducing its cost relative to private transport; encouraging vehicle usership in place of ownership; and encouraging and supporting increased levels of walking and cycling. ( CSTC, 2019 )

This, as Caroline Lucas suggests, speaks to the need to coordinate public and private transport policy more effectively and clearly, and there is a need for broader informed debate here. In political ecological circles, for example, there is a growing critique of the tensions encapsulated in the concept of an ‘environmental state’ (see Koch, 2019 ). That is the coordination and coherence of environmental imperatives with other policy concerns. State-rescaling and degrowth and postgrowth work highlight the profound problems that are now starting to emerge as states come to terms with the basic mechanisms that have been built into our economies and societies (see also Newell and Mulvaney, 2013 ; Newell, 2019 ). 38 New thinking is required and this extends to the social ontology and theory we use to conceptualise economies (see Spash and Ryan, 2012 ; Lawson, 2012 , 2019 ) and political formations (see Bacevic, 2019 ; Patomäki, 2019. Covid-19 does not change this ( Gills, 2020 ).

In transport terms, there are many specific issues to consider. Some solutions are simple but overlooked because we are always thinking in terms of sophisticated innovations and inventions. However, we do not need to conform to the logics of ‘technological fixes’, that we somehow think will enable the impossible, to perhaps see some scope in ‘fourth industrial revolution’ transformations ( Center for Global Policy Solutions, 2017 ; Morgan, 2019B ). For example, public transport may also extend to a future where no individual owns a range extensive powered vehicle (perhaps just local scooters for the young and mobility scooters for the infirm) and instead a system operates of autonomous fleet vehicles that are coordinated by artificial intelligence with logistics implemented through Smartphone calendar access booking systems—and coordination functions could maximise sharing, where vehicles could also be (given no drivers are involved) adaptable connective pods that chain together to minimise congestion and energy use. This seems like science fiction now, and perhaps a little ridiculous, but a few years ago so did the Smartphone. And the technology already exists in infancy. Such a system could be either state-funded and run or private partnership and franchise, but in either case, it radically redraws the transport environment whilst working in conformity with the geography of living spaces we have already developed. Will is what is required and if the outcome of COP24 ( UNFCCC, 2018 ) and COP25 ( Newell and Taylor, 2020 ) with limited progress towards the Paris goals persists, then it seems likely that emissions will accumulate rapidly in the near future and the likelihood of a serious climate event with socio-economic consequences rises. At that stage, more invasive statutory and regulatory intervention may start to occur as the carbon budget becomes a more urgent target. Prohibitions, transport rationing and various other possibilities may then be on the agenda if we are to unmake the future we are currently writing and, to mix metaphors, avoid a road to nowhere.

None declared

Thanks to two anonymous reviewers for extensive and useful comment—particularly regarding the systematic statement of issues in the Introduction section and for additional useful references. Jamie Morganis Professor of Economic Sociology at Leeds Beckett University, UK. He coedits the Real-World Economics Review with Edward Fullbrook. RWER is the world’s largest subscription based open access economics journal. He has published widely in the fields of economics, political economy, philosophy, sociology, and international politics. His recent books include: Modern Monetary Theory and its Critics (ed. with E. Fullbrook, WEA Books, 2020), Economics and the ecosystem (ed. with E. Fullbrook, WEA Books, 2019); Brexit and the political economy of fragmentation: Things fall apart (ed. with H. Patomäki, Routledge, 2018); Realist responses to post-human society (ed. with I. Al-Amoudi, Routledge, 2018); Trumponomics: Causes and consequences (ed. with E. Fullbrook, College Publications, 2017); What is neoclassical economics? (ed., Routledge, 2015); and Piketty’s capital in the twenty-first century (ed. with E. Fullbrook, College Publications, 2014).

Bacevic , J . 2019 . Knowing neoliberalism , Social Epistemology , vol. 33 , no. 4 , 380 – 92

Google Scholar

Bailey , I. and Wilson , G . 2009 . Theorising transitional pathways in response to climate change: technocentrism, ecocentrism, and the carbon economy , Environment and Planning A , vol. 41 , no. 10 , 2324 – 41

CCC. 2019 . Net Zero: The UK’s Contribution to Stopping Global Warming , London , Author

Google Preview

Center for Global Policy Solutions. 2017 . Stick Shift: Autonomous Vehicles, Driving Jobs and the Future of Work , Washington DC , Author

Chapman , L . 2007 . Transportation and climate change: a review , Journal of Transport Geography , vol. 15 , no. 5 , 354 – 67

China Daily. 2018, December 1 . China has 325 million motor vehicles , China Daily

Christensen , J. and Olhoff , A . 2019 . Lessons from a Decade of Emissions Gap Assessments , Nairobi , UNEP

CSTC. 2019 . Clean Growth: Technologies for Meeting the UK’s Emissions Reduction Targets , London , Author

DBEIS. 2018 . Annex: 1990–2016 UK Greenhouse Gas Emissions, Final Figures by end User , London , Author

DECC. 2015 . Different Approaches to Reporting UK Greenhouse Gas Emissions , London , Author

Deloitte. 2018 . Battery Electric Vehicles. New market. New entrants. New challenges , London , Author

Dennis , K. and Urry , J . 2009 . After the Car , Cambridge , Polity

Department for Transport. 2018 . The Road to Zero: Next Steps Towards Cleaner Road Transport and Delivering our Industrial Strategy , London , Author

Department for Transport. 2019 . Vehicle Licensing Statistics: Annual 2018 , London , Author

Dunlap , A . 2019 . Wind, coal and copper: the politics of land grabbing, counterinsurgency and the social engineering of extraction , Globalizations vol. 17 , no. 4 , 661 – 82

Environmental Audit Committee. 2016 . Sustainability in the Department of Transport [Third Report of Sessions 2016–17], London , House of Commons

Faraday Institution. 2019 . UK Electric Vehicle and Battery Production Potential to 2040 , London , Author

Faulkner , P. and Runde , J . 2013 . Technological objects, social positions and the transformational model of social activity , MIS Quarterly , vol. 37 , no. 3 , 803 – 18

Frost & Sullivan. 2019 . Global Electric Vehicle Market Outlook, 2019 , Author , London

Fullbrook , E. and Morgan , J. (eds.). 2019 . Economics and the Ecosystem , London , World Economic Association Books

Georgescu-Roegen , N . 1971 . The Entropy Law and the Economic Process , Cambridge and London , Harvard University Press

Gills , B . 2020 . Deep Restoration: from the Great Implosion to the Great Awakening , Globalizations , vol. 17 , no. 4 , 577 – 9

Gills , B. and Morgan , J . 2019 . Global Climate Emergency: after COP24, climate science, urgency, and the threat to humanity , Globalizations

Gills , B. , Morgan , J. and Patomäki , H . 2019 . President Trump as status dysfunction , Organization , vol. 26 , no. 2 , 291 – 301

Hansen , J. et al.  2017 . Young people’s burden: requirement of negative CO2 emissions , Earth System Dynamics , vol. 8 , 577 – 616

Harvey , F . 2020, March 28 . Tackle climate crisis and poverty with zeal of Covid-19 fight scientists urge , The Guardian

Hirst , D . 2019 . ‘ Electric Vehicles and Infrastructure’ , Briefing Paper no. CBP07480, London , House of Commons Library

Hoekstra , A . 2019 . The underestimated potential of battery electric vehicles to reduce emissions , Joule , vol. 3 , no. 6 , 1412 – 4

Holt , R. , Pressman , S. and Spash , C. (eds.). 2009 . Post Keynesian and Ecological Economics , Cheltenham , Edward Elgar

Holtsmark , B. and Skonhoft , A . 2014 . The Norwegian support and subsidy policy for electric cars. Should it be adopted by other countries? Environmental Science & Policy , vol. 42 , 160 – 8

IEA. 2019A . Global EV Outlook 2019: Scaling up the Transition to Electric Mobility , Paris , Author

IEA. 2019B . World Energy Outlook , Paris , Author

IPCC. 2018 . Global Warming of 1.50C: Summary for Policymakers , Geneva , Author

IPCC. 2019A . IPCC Special Report on Climate Change, Desertification, Land Degradation Sustainable Land Management Food Security and Greenhouse Gas fluxes in Terrestrial Ecosystems , Geneva , Author

IPCC. 2019B . The Ocean and Cryosphere in a Changing Climate , Geneva , Author

Koch , M . 2019 . The state in the transformation to a sustainable postgrowth economy , Environmental Politics , vol. 29 , no. 1 , 115 – 33

Lawson , C . 2012 . Aviation lock-in and emissions trading , Cambridge Journal of Economics , vol. 36 , no. 5 , 1221 – 43

Lawson , C . 2017 . Technology and Isolation , Cambridge , Cambridge University Press

Lawson , T . 2019 . The Nature of Social Reality: Issues in Social Ontology , London , Routledge

Lea , R . 2019, September 6 . Tesla Model 3 enters sales chart at No3 , The Times

Lenton , T. , Rockstrom , J. , Gaffney , O. , Rahmstorf , S. , Richardson , K. , Steffen , W. and Schellnuber , H . 2018 . Climate tipping points too risky to bet against , Nature , vol. 575 , 592 – 5

Manzetti , S. and Mariasiu , F . 2015 . Electric vehicle battery technologies: from present state to future systems , Renewable and Sustainable Energy Reviews , vol. 51 , 1004 – 12

Mattioli , G. , Roberts , C. , Steinberger , J. , and Brown , A . 2020 . The political economy of car dependence: a systems of provision approach , Energy Research & Social Science , vol. 66 , 1 – 18

Morgan , J . 2016 . Paris COP21: power that speaks the truth? Globalizations , vol. 13 , no. 6 , 943 – 51

Morgan , J . 2017 . Piketty and the growth dilemma revisited in the context of ecological economics , Ecological Economics , vol. 136 , 169 – 77

Morgan , J . 2019A . Intervention, policy and responsibility: economics as over-engineered expertise?, pp. 145 – 63 in Dolfsma , W. and Negru , I. (eds.), 2019 The Ethical Formation of Economists , London , Routledge

Morgan , J . 2019B . Will we work in twenty-first century capitalism? A critique of the fourth industrial revolution literature , Economy and Society , vol. 48 , no. 3 , 371 – 98

Morgan , J. and Patomäki , H . 2017 . Contrast explanation in economics: its context, meaning, and potential , Cambridge Journal of Economics , vol. 41 , no. 5 , 1391 – 418

Nasir , A. and Morgan , J . 2018 . The unit root problem: affinities between ergodicity and stationarity, its practical contradictions for central bank policy, and some consideration of alternatives , Journal of Post Keynesian Economics , vol. 41 , no. 3 , 339 – 63

National Audit Office. 2019 . Department of Transport Sustainability Update , London , Author

Newell , P . 2019 . Transformismo or transformation? The global political economy of energy transitions , Review of International Political Economy , vol. 26 , no. 1 , 25 – 48

Newell , P. and Mulvaney , D . 2013 . The political economy of the “just transition” , The Geographical Journal , vol. 179 , no. 2 , 132 – 40

Newell , P. and Taylor , O . 2020 . Fiddling while the planet burns? COP 25 in perspective , Globalizations , vol. 17 , no. 4 , 580 – 92

ONS. 2019 . UK Environmental Accounts: 2019 , London , Author

Patomäki , H . 2019, July 9 . ‘The Climate Movement? What’s Next?’, available at https://patomaki.fi/en/2019/07/the-climate-movement-whats-next/

Petit , S . 2017 . World vehicle population rose 2.6% in 2016 , Ward Intelligence

Regett , A. , Mauch , W. and Wagner , U . 2019 . Carbon Footprint of Electric Vehicles – A Plea for More Objectivity , available at https://www.ffe.de/attachments/article/856/Carbon_footprint_EV_FfE.pdf

Ripple , W. , Wolf , C. , Newsome , T. , Barnbard , P. , Moomaw , W. and 11,258 signatories. 2019 . World Scientists’ warning of a climate emergency , BioScience , vol. 70 , no. 1 , 8 – 12

Romare , M. and Dahlöff , L . 2017 . ‘ The Life Cycle Energy Consumption and Greenhouse gas Emissions From Lithium-Ion Batteries’ , Report No. C243, Stockholm , IVL Swedish Environmental Research Institute

Royal Academy of Engineering. 2010 . Electric Vehicles: Charged with Potential , London , Author

Servigne , P. and Stevens , R . 2015 . Comment tout peut s’efondrer , Paris , Science Humaines , available at https://www.seuil.com/ouvrage/comment-tout-peut-s-effondrer-pablo-servigne/ 9782021223316

Smil , V . 2017A . Energy and Civilization , Boston , MIT Press

Smil , V . 2017B . Energy Transitions , Colorado , Praeger

SMMT. 2019 . UK Electric Car Registrations Surge in August but it’s a Long Road to Zero and Barriers Must be Addressed , Press Release September 5th, London , Author

Spash , C. (ed.). 2017 . Routledge Handbook of Ecological Economics: Nature and Society , New York , Routledge

Spash , C . 2020 . A tale of three paradigms: realising the revolutionary potential of ecological economics , Ecological Economics vol. 169 ,

Spash , C. and Ryan , A . 2012 . Economic schools of thought on the environment: investigating unity and division , Cambridge Journal of Economics , vol. 36 , no. 5 , 1091 – 121

Staffell , I. Green , R. Gross , R. and Green , T . 2019 . How clean is my car? , Electric Insights Quarterly , vol. Q2 , 7 – 10

Statista. 2019A . Number of Motor Vehicles Registered in the United States from 1990 to 2017 (in 1000s) , [data updated June 2019], available at https://www.statista.com/statistics/183505/number-of-vehicles-in-the-united-states-since-1990/

Statista. 2019B . Car “Parc” in China from 2007 to 2018 (millions) , [data updated August 2019], available at https://www.statista.com/statistics/285306/number-of-car-owners-in-china/

Steffen , W. et al.  2018 . Trajectories of the Earth System in the Anthropocene , Proceedings of the National Academy of Sciences of the USA , vol. 115 , 8252 – 9

Taylor , M . 2015 . The Political Ecology of Climate Change Adaptation , London , Routledge/Earthscan

UNEP. 2012 . Global Environmental Outlook Report 5: Environment for the Future We Want , New York , Author

UNEP. 2018 . Emissions Gap Report 2018 , 9th ed., New York , Author

UNEP. 2019A . Emissions Gap Report 2019 , 10th ed., New York , Author .

UNEP. 2019B . Global Environmental Outlook Report 6: Healthy Planet Healthy People , New York , Author

UNFCCC. 1992 . United Nations Framework Convention on Climate Change , New York , Author

UNFCCC. 2015 . Adoption of the Paris Agreement and Annex: Paris Agreement , Paris , Author

UNFCCC. 2018 . Katowice Texts , Katowice , Author

Webster , B . 2019, June 6 . Britain “could be held to ransom” on electric cars , The Times

Williamson , K. , Satre-Meloy , A. , Velasco , K. and Green , K . 2018 . Climate Change Needs Behaviour Change: Making the Case for Behavioural Solutions to Reduce Global Warming , Arlington, VA , Centre for Behaviour and the Environment

Zheng , S . 2017, April 19 . China now has over 300 million vehicles… that’s almost America’s total population , South China Morning Post

Global electric car sales and market share, 2013–18.

Source : IEA (2019, p. 10).

ULEV refers to vehicles that emit less than 75 gCO 2 per km. This essentially means BEVs, PHEVs, range-extended (typically an auxiliary fuel tank) electric vehicles, fuel cell (non-plug-in) electric vehicles and hybrid models (non-plug in vehicles with a main fuel tank but whose battery recharges and which drive short distances in electric mode).

Note, there is little sign of legislative and regulatory detail to plans as of early 2020. Furthermore, there is a difference between acknowledging that the uptake of alternatively fuelled vehicles, including BEVs, is growing and drawing the inference that UK government policy (channelled primarily via the Department for Transport) is as effective as it might be (see Environmental Audit Committee, 2016 ; National Audit Office, 2019 and also later discussions).

CEM is coordinated by the IEA and is an initiative lead by Canada and China (but including a steadily growing number of signatory countries). The EV30@30 initiative aims to achieve a 30% annual sales share for BEVs by 2030.

IEA headline statistics include plug-in hybrids so 2018 becomes 46% for Norway (IEA, 2019A, p. 10).

For example, Spash (2020) and Spash and Ryan (2012) . One might also note the work of John O’Neill at Manchester University. Perhaps the most prominent ‘realist’ working on transport and ecology is Petter Naess, at Norwegian University of Life Sciences.

The UNEP 9th Report calls for a 55% reduction by 2030.

The initial rationale in 2008 was that to achieve a maximum limit of 2°C warming global emissions needed to fall from the levels at that time to 20–24 GtCO 2 e with an implied average of 2.1–2.6 t CO 2 per capita on a global basis in 2050. This translated to a 50–60% reduction to the then global total. Since UK emissions were above average per capita, the UK reduction required was estimated at about 80%. Given that emissions then increased and atmospheric ppm has risen the original calculations are now mainly redundant.

For the work of the CCC, see: https://www.theccc.org.uk/about/ .

The report also provides useful context regarding the UN sustainable development goals ( CCC, 2019 : p. 66) and CCC thinking on growth and economics ( CCC, 2019 : pp. 46–7).

https://www.theccc.org.uk/2019/06/11/response-to-government-plan-to-legislate-for-net-zero-emissions-target/ .

And further methodological issues apply in economics (see; Morgan and Patomäki, 2017 ; Nasir and Morgan, 2018 ; Morgan, 2019A ).

For a full analysis, see https://www.carbonbrief.org/analysis-uks-co2-emissions-have-fallen-29-per-cent-over-the-past-decade . The Carbon Brief analysis omits shipping and aviation. As the campaign group Transport and Environment notes UK shipping was responsible for 14.4 MtCO 2 , which is the third highest in Europe (after the Netherlands and Spain) and shipping is exempt from tax on fossil fuels under EU law. See p. 20: https://www.transportenvironment.org/sites/te/files/publications/Study-EU_shippings_climate_record_20191209_final.pdf .

UK coal use for energy supply reduced by approximately 90% from 1990 to 2017 and in 2019 amounted to just 2% of the energy mix and in 2019 the UK went two weeks without using any coal at all for power production (the first time since 1882); 1990 to 2010 natural gas use steadily increased from a near-zero base but has declined since 2010 as use of renewables has grown. Coal use in manufacturing has decreased by 75% from 1990 to 2017 ( ONS, 2019 ). As noted, some assessments place the reduction in total emissions at around 40% based on other metrics and the tabulated figures I provide indicate yet another percentage— all however are trend decreases indicative of a general direction of travel.

‘Embedded emissions’ or the UK carbon footprint is addressed by the UK Department for Environment Food and Rural Affairs (Defra). To be clear, there is a whole set of further issues that one might address in regard of measurement of emissions—how they are attributed and what this means (where created, where induced through demand, which state, what corporation and so different ‘Cartesian’ claims regarding the significance of location are possible), and this is indicative of the conflict over representation and partition of responsibility (so whilst the climate does not care about borders, they have infected measurement and policy). There is no scientifically neutral way to achieve this, merely different sets of criteria with different consequences (I thank an anonymous referee for extended comment on this, see also Taylor, 2015 ; who argues that adaptation politics produces a focus on governance within existing political and economic structures based on borders, etc.).

Congestion charges in London or a plastic bag tax do not meet this threshold.

This is supported, for example, by The Climate Group’s EV100 initiative: a voluntary scheme where corporations commit to making electric the ‘new normal’ of their vehicle fleets by 2030 (recognising that over half of annual new registrations are owned by businesses) https://www.theclimategroup.org/project/ev100 .

Until recently Tesla had one main production centre in California. However, it now also has a $5 billion factory in Shanghai and plans for a factory in Berlin. Tesla is currently the world’s largest producer of BEVs (368,000 units in 2019), followed by the Chinese company BYD Auto (195,000 units in 2019). Tesla was founded in July 2003 by Martin Eberhard and Mark Tarpenning in response to General Motors scrapping its EV programme (as unprofitable). Elon Musk joined as a HNWI first-round investor in February 2004 (he put in $6.5 m of the total $7.5 m and became chairman of the Tesla board); Eberhard was initially CEO but was removed and replaced by Musk in 2007 and Tarpenning left in 2008. Tesla floated on the Nasdaq in June 2010 at $17 per share and exceeded $500 per share for the first time in January 2020. Tesla is the USA’s most valuable car manufacturer by market capitalisation (worth more than Ford and GM combined).

The European Commission’s collaborative research forum JEC has been producing ‘well-to-wheels’ analyses of energy efficiency of different engine technologies since the beginning of the century. The USA periodically publishes the findings of its GREET model (the Greenhouse gases Regulated Emissions and Energy use in Transportation model). See https://greet.es.anl.gov .

For example, since 1985 according to Carbon Brief global coal use in power production measured in terawatt hours only reduced in 2009 and 2015 (though it seems likely to do so in 2019); China notably continues to build coal-fired power plants though the rate of growth of use has slowed. (According to the IEA Coal report, 2019, China consumed 3,756 million tonnes of coal in 2018 (a 1% increase) and India 986 million tonnes (a 5% increase). Renewables are a growing part of an expanding global energy system.

https://www.carbonbrief.org/analysis-global-coal-power-set-for-record-fall-in-2019 .

Staffell et al . observe that the British electricity grid produces an average 204 gCO 2 per kWh in 2019 and a standard petrol car emits 120–160 gCO 2 per km.

This is a point made by Richard Smith. There are, of course, alternatives to aluminium. One should also note that manufacturers are responding to consumer preference by increasing the average size of models and this is increasing the weight and resource use. In February 2020, for example, Which Magazine analysed 292 popular car models and found that they were on average 3.4% or 67 kg heavier than older models and this was offsetting some of the efficiency gains for emissions.

And the argument this is leading to is that it makes far greater sense to default to greater dependence on prudential social redesign, rather than optimistic technocentrism, behind which is techno-politics.

For discussion of battery technology and scope for improvement, see Manzetti and Mariasiu (2015) and Faraday Institution (2019) . Currently, most BEVs use lithium-ion phosphate, nickel-manganese cobalt oxide or aluminium oxide batteries. Liquid electrolyte constituents require containment and shielding. Specifically, a battery creates a flow of electrons from the positive electrode (the cathode made of a lithium metal oxide, etc. from the previous list) through a conducting electrolyte medium (lithium salt in an organic solution) to a negative electrode (the anode made typically of carbon, since early experiment with metals tended to produce excess heating and fire). This creates a current. Charging flows to the anode and discharge oxidises the anode which must then be recharged. The batteries are relatively low ‘energy density’ and can be a fire hazard when they heat. Given the chemical constituents, battery disposal is also a significant environmental hazard (see IEA, 2019A: pp. 8, 22–3). A ‘solid-state’ battery uses a specially designed (possibly glass or ceramic) solid medium that allows ions to travel through from one electrode to another. The solid-state technology is in principle higher energy density, much lighter and more durable. The implication is higher kWh batteries with greater range, charging capacity and durability and efficiency. Jeremy Dyson has reportedly invested heavily in solid-state technology and though his proposed own brand BEV is not now going ahead, reports indicate the battery technology investment will continue.

One might also consider hydrogen battery technology. Hydrogen fuel cell technology for vehicles is different than BEV. The vehicle has a tank in the rear for compressed cooled gas, which supplies the cell at the front of the car whilst driving. Refuelling is a rapid pumping process rather than a long wait. The gas has two possible origins: natural gas conversion where ‘steam methane reformation’ separates methane into hydrogen and CO 2 or water electrolysis, where grid AC electricity is converted to DC, which is applied to water and using a membrane splits it into hydrogen and waste oxygen. Currently, over 95% of hydrogen is from the former. Major investors in hydrogen technology are Shell (for natural gas conversion), IMT Power (in partnership with Shell) for water conversion and Toyota whose Mirai model is hydrogen powered.

Though fewer new cars were registered than in previous years, this significant metric for the total number of vehicles is the cumulative number of registrations (taking into account cars no longer registered). There are, however, some underlying issues: uncertainty regarding the status of diesel cars and problems of availability, cost and trust in BEVs seems to be causing many people in the UK to delay buying a new car; the expansion of Uber meanwhile has had a generational and urban effect, reducing car ownership as an aspiration amongst the young.

And re aviation, a new runway at Heathrow between 2026 and 2050.

See: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/852708/provisional-road-traffic-estimates-gb-october-2018-to-september-2019.pdf .

See: https://greenworld.org.uk/article/budget-deeply-disappointing-says-caroline-lucas

For example, global production of cobalt in 2018 was 120,000 tonnes, and production of about 2 million BEVs currently requires around 25,000 tonnes, so 10 million BEVs would require all of the current output. Cobalt traded at more than US$90,000 per ton 2018 but had fallen to around US$30,000 at the end of 2019.

In the UK, the current daily consumption of petrol and diesel for road transport is about 125 million litres or about 45 billion litres per year. So, BEVs are essentially substituting for this scale of energy use, shifting demand to electricity generation. National Grid attempted to model this in 2017. Their forecast (highly contingent obviously) suggests that if all cars sold by 2040 were BEVs and thus the car market was dominated by BEVs by 2050 and if most vehicles were charged at peak times in 2050 then an additional 30 gigawatts of electricity would be required. This is about 50% greater than the current peak winter demand in 2017. This was widely reported in the press. This best/worst case, of course, does not allow for innovative solutions such as off-peak home charging pioneered by Ovo and other niche suppliers. However, even with such solutions, there will still be a net increase in required capacity from the system. This has been estimated at about 10 new Hinckley power stations.

One possible long-term solution currently in development is toughened solar panel devices that can be laid as a road or car park surfaces, enabling contact recharging of the vehicle (in motion or otherwise). There are, however, multiple problems with the technology so far.

For example, analysis from Capital Economics suggests a three-way charging split is likely to develop: home recharging is likely to dominate, followed by an on-route charging model (substituting for current petrol forecourts at roadside) and destination recharging (given charging is slower than filling a fuel tank it makes sense to transform car parks at destinations into charging centres—supermarkets, etc.). They estimate UK demand at 25 million BEV chargers by 2050 of which all but 2.6 million will be home charging. As of early 2020, there were 8,400 filling stations which might be fully converted. Tesco has a reported commitment to install 2,400 charging points. These are issues frequently reported in the press.

This point can also be made in other ways. Not only does the emissions saving relate to net new sources of cars, but the contrast is also in terms of trend changes in the size of vehicle. According to the recent IEA World Energy Outlook report ( IEA, 2019B ), the number of SUVs is increasing and these consume around 25% more fuel than a mid-range car. If current growth trends continue (SUVs are 42% of new sales in China, 30% in India and about 50% in the USA), the IEA projects that the take-up of ICE SUVs will more than offset any marginal gains in emissions from the transition to BEVs.

It is also the case that the projected ‘savings’ from ULEVs are likely inaccurate. Following the EU, most countries adopted (and manufacturers report using) the Worldwide Harmonised Light Vehicle Test Procedure (WLTP). This became mandatory in the UK from September 2018. The WLTP is the new laboratory defined test for car distance-energy metrics. Vehicles are tested at 23°C, but without associated use of A/C or heating. Though claimed to as realistic than its predecessors, it is still basically unrealistic. Temperature range for ULEVs has significant consequences for battery performance and for use of on-board services, so real distance travelled per unit of energy is liable to be less. For similar reasons, ICEs will also travel less distance per litre of fuel so this is not a comparative gain for ICEs, it is likely a comparative loss to all of us if we rely on the figures.

See https://www.theccc.org.uk/2018/07/10/road-to-zero-a-missed-opportunity/ .

See https://www.theccc.org.uk/2018/07/10/governments-road-to-zero-strategy-falls-short-ccc-says/ .

See https://www.weforum.org/agenda/2019/08/shared-avs-could-save-the-world-private-avs-could-ruin-it/ .

For practical network initiatives, see, for example, https://climatestrategies.org .

Email alerts

Citing articles via.

• Contact Cambridge Political Economy Society
• Recommend to your Library

Affiliations

• Online ISSN 1464-3545
• Print ISSN 0309-166X
• Copyright © 2024 Cambridge Political Economy Society
• About Oxford Academic
• Publish journals with us
• University press partners
• What we publish
• New features  
• Open access
• Institutional account management
• Rights and permissions
• Get help with access
• Accessibility
• Advertising
• Media enquiries
• Oxford University Press
• Oxford Languages
• University of Oxford

Oxford University Press is a department of the University of Oxford. It furthers the University's objective of excellence in research, scholarship, and education by publishing worldwide

• Copyright © 2024 Oxford University Press
• Cookie settings
• Cookie policy
• Privacy policy
• Legal notice

This Feature Is Available To Subscribers Only

Sign In or Create an Account

This PDF is available to Subscribers Only

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Advertisement

Supported by

How China Built Tech Prowess: Chemistry Classes and Research Labs

Stressing science education, China is outpacing other countries in research fields like battery chemistry, crucial to its lead in electric vehicles.

• Share full article

By Keith Bradsher

Reporting from Changsha, Beijing and Fuzhou, China

China’s domination of electric cars, which is threatening to start a trade war, was born decades ago in university laboratories in Texas, when researchers discovered how to make batteries with minerals that were abundant and cheap.

Companies from China have recently built on those early discoveries, figuring out how to make the batteries hold a powerful charge and endure more than a decade of daily recharges. They are inexpensively and reliably manufacturing vast numbers of these batteries, producing most of the world’s electric cars and many other clean energy systems.

Batteries are just one example of how China is catching up with — or passing — advanced industrial democracies in its technological and manufacturing sophistication. It is achieving many breakthroughs in a long list of sectors, from pharmaceuticals to drones to high-efficiency solar panels.

Beijing’s challenge to the technological leadership that the United States has held since World War II is evidenced in China’s classrooms and corporate budgets, as well as in directives from the highest levels of the Communist Party.

A considerably larger share of Chinese students major in science, math and engineering than students in other big countries do. That share is rising further, even as overall higher education enrollment has increased more than tenfold since 2000.

Spending on research and development has surged, tripling in the past decade and moving China into second place after the United States. Researchers in China lead the world in publishing widely cited papers in 52 of 64 critical technologies, recent calculations by the Australian Strategic Policy Institute reveal.

We are having trouble retrieving the article content.

Please enable JavaScript in your browser settings.

Thank you for your patience while we verify access. If you are in Reader mode please exit and  log into  your Times account, or  subscribe  for all of The Times.

Thank you for your patience while we verify access.

Already a subscriber?  Log in .

Want all of The Times?  Subscribe .

Why are EV sales slowing?

Sales momentum for electric vehicles (EVs) is slowing globally, and hybrids (HEVs) and plug-in hybrids (PHEVs) are proving more competitive than first thought.

As sales flag, Goldman Sachs Research analyst Kota Yuzawa says the team’s bear case for EV sales is becoming more likely. At the same time, he sees investment opportunities in automakers with strong balance sheets and lineups with multiple powertrains. The team also expects demand for EVs to gradually grow amid the pursuit of carbon neutrality.

We spoke with Kota for his views on where the global EV market is headed.

What are the headwinds for the EV market?

We believe there are three main factors blunting EV penetration. For one, we’re seeing rising concerns around EV capital costs due to lower prices being realized for used EVs. In the UK, for example, EV used car prices have fallen sharply in recent months. Two, uncertainty around a number of elections this year has decreased visibility on potential changes to government policies affecting the EV industry.

The third and final concern is around a shortage of rapid-charging stations. As EV penetration accelerates, rapid charging station infrastructure issues have emerged as a tangible problem. Several automakers have said that concerns about driving range and charging infrastructure are increasing. These issues may lead consumers to have second thoughts about buying an EV.

How has the EV slowdown impacted your forecasts?

We think our bear scenario calling for a year-over-year decline in EV sales volume in 2024 has become more realistic given the three negative factors outlined above. We previously suggested that EV penetration could vary considerably under various conditions. Despite the current slowdown in EVs, our base-case scenario still calls for EV sales volume to rise 21% year-over-year in 2024. But under our bear-case scenario, we see EV sales volume declining 2% year-over-year, and negative growth would likely result in oversupply across the EV supply chain.

What’s going on with hybrid sales?

Sales of HEVs and PHEVs have been accelerating amid the slowdown in EVs. In the US, growth has outpaced EVs over the past several months. As a result, we believe global HEV sales could exceed the outlook by 1 to 2 million vehicles. While HEVs are viewed as transitional technology, we look for increasing focus on them to help reduce CO2 while maximizing earnings and supporting investment in EVs for automakers.

HEVs have a significant advantage in payback period compared to EVs. We estimate the payback period for HEVs at just over three years, assuming annual fuel savings. In addition, given that the first HEVs were introduced back in 1997, we believe there is high confidence in used car prices for HEVs.

But we also believe HEVs may not be chosen solely because of their economic rationality. In fact, hybrids have shown higher horsepower performance than gasoline-engine vehicles. Motor assistance when accelerating is likely to provide reassurance to drivers when, for example, they need to merge into fast-moving traffic on highways. Amid the downsizing of gasoline engines, we think HEV performance could garner greater attention. But if lower EV costs are realized by 2030, we believe the advantages of EVs will again come under focus.

How is China impacting the global EV market?

With excess production capacity currently at more than 5 million vehicles, China aims both to expand domestic EV uptake and export EVs to overseas markets. China enjoys cost advantages given its concentrated EV supply chain (including for batteries), and we think it is also the most competitive in lithium iron phosphate batteries.

Many government policies in the US, Europe, and India seek to block Chinese and other foreign EVs from gaining a foothold in their EV supply chains, to the degree possible. Given that EV demand outside China is not very large apart from these three regions, we think it’s unlikely that China’s supply surplus will be eliminated easily. As Chinese EV makers face a challenging overall landscape when it comes to exports, it is becoming more important to keep a closer eye on winners and losers among them.

Chinese EV makers do pose a major threat to Japanese brands, which have maintained high market share in Southeast Asia for many years. The Southeast Asia market has been a major export destination for Chinese EVs since 2023.

What does all this mean for investors? What types of companies should they seek?

Now is the time for upfront investment in vertical integration. As we expect demand will eventually shift to EVs in pursuit of achieving carbon neutrality, we believe it will be important for automakers to move decisively over the next few years to accumulate core EV technologies (batteries, power semiconductors, motors, etc.). We also think balance sheet strength and the ability to generate free cash flow from existing businesses will be crucial in supporting this ongoing investment. We are bullish on automakers with strong balance sheets and lineups with multiple powertrains, such as HEVs.

This article is being provided for educational purposes only. The information contained in this article does not constitute a recommendation from any Goldman Sachs entity to the recipient, and Goldman Sachs is not providing any financial, economic, legal, investment, accounting, or tax advice through this article or to its recipient. Neither Goldman Sachs nor any of its affiliates makes any representation or warranty, express or implied, as to the accuracy or completeness of the statements or any information contained in this article and any liability therefore (including in respect of direct, indirect, or consequential loss or damage) is expressly disclaimed.

Our weekly newsletter with insights and intelligence from across the firm

By submitting this information, you agree to receive marketing emails from Goldman Sachs and accept our  privacy policy . You can opt-out at any time.

How European consumers perceive electric vehicles

Electric vehicles (EVs) are no longer a niche business. They now account for 16 percent of new-car sales in Europe, up from under 1 percent in 2019. Despite the removal of purchase subsidies in certain markets, such as Germany at the end of 2023, sales have remained stable. Since the beginning of 2024, more than 875,000 new full battery electric vehicles (BEVs) have been sold across the continent.

About the authors

This article is a collaborative effort by Andreas Venus , Patrick Schaufuss , and Timo Möller , with Anna-Sophie Smith, Felix Rupalla, Jan Paulitschek, and Laura Solvie, representing views from the McKinsey Center for Future Mobility.

As EV growth continues to unfold in Europe , automakers are developing more nuanced profiles of the average EV buyers they are targeting. Some buyers are innovators, or early adopters, who opted for EVs years ago and are now on their second or third purchase. Although this segment remains important, the EV customer base is also expanding to include more mainstream customers who have different expectations for EVs .

To understand European consumers’ views on EVs and key market trends, we recently polled 15,034 individuals in France, Germany, Italy, and Norway as part of our regular McKinsey Mobility Consumer Pulse Survey, which closely monitors consumer perceptions about the future of mobility in general (see sidebar, “About the survey,” for more on our methodology). We combined insights from the survey with mobility research to analyze EV uptake patterns, identify major consumer concerns, explore perceptions of incumbents and new entrants, and investigate the used-EV market.

Electrification momentum continues across Europe

About the survey.

The 2024 McKinsey Mobility Consumer Pulse Survey was conducted online in February 2024. It involved 36,954 current mobility users across nine markets: Australia, Brazil, China, France, Germany, Italy, Japan, Norway, and the United States.

Electrification is attracting much consumer interest in Europe. Of the car buyers in our survey who have not yet purchased an EV, 38 percent say their next vehicle will be electric. A little less than half of these potential buyers plan to buy a BEV, with the rest opting for plug-in hybrid electric vehicles (PHEVs) (Exhibit 1).

Intent to purchase an EV is slightly higher in the premium-brand segment, as well as among younger and more progressive urban customers, who tend to be environmentally conscious. But interest in EVs is now expanding beyond these groups, and the next wave of buyers may include more older consumers with comparatively lower budgets. In other words, more mainstream buyers could follow the first movers who initially adopted EVs. As the consumer base shifts, customer expectations for EVs will also evolve and manufacturers must be prepared to meet them.

Intent to purchase an EV is slightly higher in the premium-brand segment, as well as among younger and more progressive urban customers, who tend to be environmentally conscious.

The major concerns of EV buyers include battery range, costs, and charging infrastructure

While almost 80 percent of European car buyers in our survey expect to get an EV in the future, 22 percent remain skeptical about these vehicles. Our survey suggests that the main reasons preventing skeptics from considering EVs involve high purchase prices, the inability to charge at home, and concern about real battery driving range—the actual driving range for a mix of trips and conditions, compared with a vehicle’s advertised cycle range based on the worldwide light-vehicle test procedure (WLTP).

Among prospective buyers who do not yet own a BEV, the main concerns about EVs are slightly different from those that the EV skeptics have, especially home charging access being less of a concern. High purchase prices topped the list (37 percent), followed by insufficient battery driving range (36 percent), and battery lifetime (35 percent) (Exhibit 2). Many respondents are also concerned about increases in electricity prices and availability of public charging infrastructure (28 percent for both). Overall, sustainability had a minor influence on purchase decisions.

The survey findings suggest that a longer driving range could accelerate BEV adoption in Europe, since buyers in this region have high expectations for the real battery driving range. In our survey, consumers who would consider an EV but have not yet purchased one state that the driving range would need to be about 500 kilometers for them to switch from an internal combustion engine (ICE) vehicle to a fully electric BEV (Exhibit 3). Among current BEV owners, expectations for driving range are only slightly lower, at about 470 kilometers.

The survey findings suggest that a longer driving range could accelerate BEV adoption in Europe.

Almost all current BEV owners now have a shorter real driving range than they stated they would need before their vehicle purchase. In our survey, only 42 percent of existing BEV owners in Europe are satisfied or very satisfied with their car’s real driving range; for those who would consider switching back to ICE vehicles, this percentage fell to 30 percent. What’s more, most of the dissatisfied respondents indicate that they are likely to switch to an ICE vehicle, rather than search for an EV with a greater driving range.

Regarding charging infrastructure, consumers have concerns that go beyond public availability. More than 75 percent of prospective BEV buyers in our survey expect public charging times of under 30 minutes to take their remaining battery power from 20 to 80 percent.

Varied preferences for vehicle features and purchases

Our survey also looked at vehicle characteristics and purchase preferences that are unrelated to electrification, and it uncovered some important differences between potential EV buyers and those sticking with traditional ICE cars. First, EV buyers place higher importance on advanced-driver-assistance systems (ADAS) with increasing degrees of autonomy (for example hands-off driving assistance features at highway speed or fully autonomous parking pilots) and comprehensive in-car connectivity offerings. This preference is characteristic of younger, more tech-enthused buyers, and many customers in this segment may prefer EVs because they view them as having more innovative technology than traditional cars. Second, 25 percent of prospective EV buyers show high interest in buying their next car online. Interest was greatest in the premium segment (34 percent).

A quarter of prospective EV buyers show high interest in buying their next car online.

ICE buyers and traditional car adherents do share one characteristic, however. In both groups, 83 percent say that they would not buy an EV without taking a test drive, indicating that this step remains a critical part of the purchase journey.

The EV transition is fully under way

The EV transition in Europe is fully under way, and our survey findings highlight three trends that may influence future adoption rates:

• a willingness to switch back to traditional ICE vehicles in a small share of EV owners
• the emergence of several new market entrants, including Chinese auto brands and other foreign OEMs, offering a wide range of new models that are already attracting interest among European customers
• the tendency for new-EV car sales to scale more quickly than used-EV sales

A minority of current EV owners would consider switching back to ICE vehicles

While the overall outlook for electrification is positive, our survey reveals that 19 percent of current EV owners in Europe say they are likely or very likely to switch back to a traditional combustion engine at their next purchase because of their current EV ownership experience (Exhibit 4). This is a reality check, but it must be considered in context. Globally, 29 percent of EV owners in our survey say they are very likely to switch back to an ICE vehicle at their next purchase, so Europeans are less likely to revert to traditional cars than people in other regions.

The reasons for switching back to an ICE vehicle are multilayered and somewhat interlinked. In our survey, the top issues relate to the following factors:

• Total cost of ownership. Today, 45 percent of European car owners are keeping their current vehicles for longer periods because of their financial situation. For EV owners, 40 percent indicate that they need to trade down with their next vehicle for the same reason. Survey respondents also express concern that selected subsidies for EVs are being reduced or eliminated in some European markets. Of the EV owners who are considering a switch back to ICE vehicles, 41 percent say that the cost of EV ownership is too high. (Their return to ICE vehicles could occur shortly, since they are closer to buying their next vehicle than other respondents, and 40 percent are planning to purchase a vehicle in 2024.) If they do, they may find that the residual value of their current EV is lower than expected and that demand for used EVs is relatively low compared with that for traditional cars.
• Underdeveloped public charging infrastructure. In our survey, 40 percent of current BEV owners in Europe state that the number of public EV charge points is insufficient. Only about 10 percent of BEV owners feel that the current charging infrastructure is ready to meet future demand; an additional 50 percent feel that it can meet current needs but believe that there will not be enough public charging stations if more EVs hit the road.
• Impact on long-distance travel. In our survey, 29 percent of respondents say they are concerned about the impact of charging on longer-distance trips. In general, longer trips in a full battery EV require owners to change their travel patterns slightly, which may seem disruptive or stressful; some may have to begin planning their charging stops before a trip begins, especially on unknown routes. Some EV owners feel that searching for free and working charge points is disruptive, with 26 percent reporting that this makes travel more stressful. For millennials and owners with children, the need to find charge points, combined with potential alterations to long travel routes, may feel particularly burdensome. These groups may therefore be more likely to consider switching back to an ICE vehicle.

When asked what values they seek in a car, EV owners who consider switching back to ICE vehicles place more value on having practical vehicles that allow them greater independence when planning routes. These factors may outweigh the positive ecological benefits of EVs. In fact, only about half of those who consider switching back to ICE vehicles state that sustainability concerns are guiding their behavior, compared with well over 60 percent of EV owners who intend to stay with electric technology. EV owners who consider returning to traditional cars are also three times more likely to state that vehicle acceleration and driver performance did not meet expectations, compared with those who do not plan to switch back.

New BEV market entrants are attracting customer interest

New players are entering European EV markets. In the past three years alone, more than 35 new OEMs have started selling battery electric vehicles in Europe, and many more have announced market-entry plans. In total, OEMs have announced that over 400 new EV models will hit the European market  over the next three years. Many new market entrants have established auto brands in Asia or North America, and several homegrown Chinese brands have also entered the market recently.

Prospective buyers are increasingly considering non-European brands, and our survey shows that EV owners are broadening their considered set of brands for purchase. European brands such as BMW, Mercedes-Benz, Renault, and Volkswagen are still the most popular, with 51 percent of EV owners stating that they are likely to purchase from them. Southeastern Asian brands such as Hyundai, KIA, and Toyota were in second place with 39 percent, followed by American brands such as Cadillac, Rivian, and Tesla (30 percent) and Chinese brands such as BYD, Li Auto, NIO, and Xpeng (27 percent).

The new entrants offer BEV models in various vehicle segments, and many cater to the average potential EV buyer’s need for more real driving range and faster charging. Some of the new models also offer innovative car features, including those that enhance interior comfort, entertainment, and in-car digital experiences. If consumers view the new brands positively and adopt them, domestic auto brands could face challenges.

Customers’ willingness to buy an emerging brand differs by country and segment (Exhibit 5). In the premium-brand segment, for instance, 33 percent of European respondents considering EVs state that they would be open to purchasing a Chinese brand  in the future. Given the European Union’s recent decision to impose tariffs on imported EVs from China, it is still uncertain how successful such new EV brands will be in Europe.

Insights on Chinese brands

Compared with American brands and other Asian brands, Chinese OEMs have relatively low name recognition in Europe. In our survey, 55 to 80 percent of European respondents had never heard of them. Consumers who were more likely to know about Chinese brands included existing EV owners, younger people, and drivers of premium cars. We decided to investigate these brands more thoroughly by conducting interviews with more than 500 European customers during their visits to a car clinic earlier this year; we asked about ten Chinese EV models. This allowed us to gather qualitative feedback from potential EV buyers as they evaluated Chinese EV models. We also gained insights about their views on other brands in the process.

Both our survey and car clinic research suggest that European consumer perceptions of Chinese brands are often different from their perceptions of domestic brands. For instance, consumers view domestic brands with pride and consider them to be safe, well designed, high quality, comfortable, and trustworthy. Consumers also value the established dealer and service networks for domestic brands, as they provide convenient customer proximity. If customers are purchasing an EV for the first time, they might feel more confident going with a known brand from an established domestic OEM, especially if they have experience with ICE vehicles from the same company.

In contrast, survey respondents tend to be skeptical about product quality and data security for new market entrant brands from China, although they do perceive them as offering good value for the money. The customers we interviewed at car clinics had similar concerns about Chinese brands, but after seeing the vehicles in person, they were also impressed by their innovative features and cutting-edge technologies, such as comfortable interiors, voice assistants’ conversational intelligence, and high-end multimedia offerings with advanced sound and displays. As more European consumers get direct experience with Chinese brands, they could develop higher expectations for the in-vehicle experience, including comfortable seating and smart-vehicle features, in all cars. Those who purchase EVs may particularly appreciate in-vehicle technologies because they may often use them when their vehicles are charging.

Our survey also showed that consumers had specific price expectations for EVs, which could affect their adoption rates. With Chinese brands, for instance, consumers generally expect the purchase price to be lower than that of similar offerings from domestic brands. In our survey, about half of European respondents say that they would only consider purchasing a Chinese EV if its price was at least 15 percent below that of a similar domestic model. Roughly a quarter of European respondents say they would seek a price advantage of up to 10 percent, and only 25 percent would not require a price advantage.

Customer views of used electric vehicles

The used-car market is another piece in the chain for further sustained EV adoption throughout Europe. While EVs accounted for more than 15 percent of new-car sales in this region in 2023, they represented less than 2 percent of used-car sales.

In our survey, 31 percent of prospective EV buyers say they are likely or very likely to consider a used EV for their next vehicle purchase—up from about 25 percent in December 2021 (Exhibit 6). For those customers still skeptical about EVs, the main concern—cited by 49 percent of respondents—was unclear battery degradation over a vehicle’s lifetime. Other concerns relate to high prices (33 percent), unclear maintenance and repair availability (26 percent), and fear of missing out on the latest EV technology (13 percent).

Many respondents also cite unclear resale value as an issue—an understandable finding, given how rapidly EV technology is evolving. In our survey, 20 percent of BEV owners say they are concerned about retail value, compared with only 10 percent of prospective buyers.

OEMs could help alleviate some consumer concerns by offering guarantees about battery degradations, vehicle checkup, or remote upgrades for digital services. Meanwhile, consumer fears about missing out on the latest technology  may fall as the EV market matures. Both developments could accelerate EV adoption in the used-car market.

As Europe accelerates its efforts to decarbonize, and the auto industry transitions from combustion engines to electric powertrains, consumer purchasing habits and expectations are changing in tandem. The overall EV outlook for Europe remains positive: consumers want a better customer experience and fewer hurdles to adoption, especially those related to public charging infrastructure readiness, real battery range, and purchase price. Addressing these issues could help take EV growth to new heights and accelerate electrification throughout Europe.

Andreas Venus is a senior partner in McKinsey’s Berlin office; Patrick Schaufuss is a partner in the Munich office, where Anna-Sophie Smith is an asset leader, Jan Paulitschek is a research science specialist, and Laura Solvie is a consultant; Timo Möller is a partner in the Cologne office; and Felix Rupalla is a senior asset leader in the Stuttgart office.

This article was edited by Belinda Yu, an editor in McKinsey’s Atlanta office.

Explore a career with us

Related articles.

Winning in the European automotive industry: A micromarket approach

Automotive R&D transformation: Optimizing gen AI’s potential value

What technology trends are shaping the mobility sector?

• Electric Cars /

An analysis of 20,000 EV stations concludes that charging is still a massive bummer

Proposed solutions to help make the ev charging experience in the us better include getting oems and network providers to work closely together..

By Umar Shakir , a news writer fond of the electric vehicle lifestyle and things that plug in via USB-C. He spent over 15 years in IT support before joining The Verge.

Share this story

The experience of charging an electric vehicle in the US could be better, and a big new study is out that lists the biggest infrastructure pain points, including a failure to report broken stalls, inaccurate station status messages, aging equipment, and some habitually unreliable network providers (who go unnamed in the study, unfortunately).

The study was conducted by the company ChargerHelp, which offers EV charger operations and maintenance solutions. The firm also had its findings reviewed and confirmed by Professor Gil Tal, who is director of the Electric Vehicle Research Center at UC Davis. ChargerHelp used four years of data from the 20,000 chargers it monitors, comparing networked stations’ self-reported uptime against the actual uptime EV drivers find on location.

EV chargers can break in many ways, the study concludes. These include broken retractor systems intended to protect the cable from getting mangled by vehicle tires, broken screens, and inoperable payment systems. There is also general damage to the cabinet and, of course, broken cables and connectors.

Across the chargers recorded, ChargerHelp calculates that actual uptime is only 73.7 percent, compared to the 84.6 percent self-reported by the EV network providers.

The study found that 26 percent of all stations analyzed did not positively match the perceived status of the chargers as presented in the networks’ software. That means some charge networks overstate the number of stations it has that are online, which puts a damper on the confidence EV owners should have in the charging infrastructure. It’s especially problematic when one badly needs a charge and ends up at a station that an app said was online but wasn’t.

Zombies and Ghosts

The study lists various situations where an EV driver can’t successfully connect with a charger, including “ghost” station scenarios, where stalls appear in an app but either don’t exist or are broken. The study also describes “zombie stations,” which exist and work but don’t appear in the apps, so drivers don’t go to them. And “confused occupancy” is when an app tells drivers certain stalls are available, but they aren’t. “Dead ends” seem all gravy until you plug in and find out it doesn’t work. ChargerHelp claims reliable software interoperability and network data sharing can help fix these issues.

There are also surprising variations in charger downtime based on location. For instance, at 4.4 percent, New Jersey had some of the lowest number of down ports in the country at the start of 2023. However, the state only had 27 working public charge ports per 1,000 registered EVs, which might not satisfy demand. Contrast that with Washington, DC, which had almost 11 percent down ports, yet had 137 ports per 1,000 registered EVs.

Long-time Google exec Susan Wojcicki has died at 56

D23 2024: all the biggest trailers and news out of disney’s biennial showcase, signal has been blocked by venezuela and russia, avatar: fire and ash hits theaters next december, nearly everyone working on nova launcher has been laid off.

More from this stream All the news about EV charging in the US

Mercedes-benz’s 400kw ev chargers are coming to starbucks, home generator company generac just launched an electric vehicle charger, ford’s answer to texas blackouts: loads of generators on wheels., toyota rolls into the ionna ev charging joint venture..

• Election 2024
• Entertainment
• Newsletters
• Photography
• AP Buyline Personal Finance
• AP Buyline Shopping
• Press Releases
• Israel-Hamas War
• Russia-Ukraine War
• Global elections
• Asia Pacific
• Latin America
• Middle East
• Delegate Tracker
• AP & Elections
• 2024 Paris Olympic Games
• Auto Racing
• Movie reviews
• Book reviews
• Financial Markets
• Business Highlights
• Financial wellness
• Artificial Intelligence
• Social Media

Japan rivals Nissan and Honda will share EV components and AI research as they play catch up

Nissan Chief Executive Makoto Uchida, left, and Honda Chief Executive Toshihiro Mibe shake hands during a joint news conference in Tokyo, Thursday, Aug. 1, 2024. Japanese automakers Nissan and Honda say they plan to share components for electric vehicles like batteries and jointly research software for autonomous driving. (Kyodo News via AP)

FILE - Logos at a Nissan showroom are seen in Ginza shopping district in Tokyo, March 31, 2023. (AP Photo/Eugene Hoshiko, File)

FILE - Logos of Honda Motor Co. are pictured in Tsukuba, northeast of Tokyo, on Feb. 13, 2019. (Kyodo News via AP, File)

• Copy Link copied

TOKYO (AP) — Japanese automakers Nissan and Honda say they plan to share components for electric vehicles like batteries and jointly research software for autonomous driving.

A third Japanese manufacturer, Mitsubishi Motors Corp., has joined the Nissan-Honda partnership, sharing the view that speed and size are crucial in responding to dramatic changes in the auto industry centered around electrification.

A preliminary agreement between Nissan Motor Co. and Honda Motor Co. was announced in March .

After 100 days of talks, executives of the companies evinced a sense of urgency. Japanese automakers dominated the era of gasoline engines in recent decades but have fallen behind formidable new players in green cars like Tesla of the U.S. and China’s BYD.

“Companies that don’t adapt to the changes cannot survive,” said Honda Chief Executive Toshihiro Mibe. “If we try to do everything on our own, we cannot catch up.”

Nissan and Honda will use the same batteries and adopt the same specifications for motors and inverters for EV axels, they said.

By coming together in what Mibe and counterpart at Nissan, Makoto Uchida, repeatedly called “making friends” to achieve economies of scale, the companies plan more strategic investments in technology and aim to cut costs by boosting volume.

Each company will continue to produce and offer its own model offerings. But they will share resources in areas like components and software development, where “making friends” will be a plus, Mibe and Uchida told reporters.

They declined to say whether the friendship will extend to a mutual capital ownership, while noting that wasn’t ruled out.

The two companies also agreed to have their model lineups “mutually complement” each other in various global markets, including both internal combustion engine vehicles and EVs. Details on that are being worked out, the companies said.

Honda and Nissan will also work together on energy services in Japan. Under Thursday’s announcements, Mitsubishi will join as a third member.

Toyota Motor Corp. , Japan’s top automaker, is not part of the three-way collaboration.

Although Honda and Nissan have very different corporate cultures, it became clear, as their discussions on working together continued, their engineers and other workers on the ground have a lot in common, Uchida said.

“Speed is the most crucial element, considering our size,” he added.

Uchida and Mibe repeatedly stressed speed, openly admitting BYD is moving very quickly, but they said there was still time to catch up and remain in the game.

“In coming together, we will show that one plus one will add up to become more than two,” Uchida said.

Yuri Kageyama is on X: https://twitter.com/yurikageyama

• Skip to main content
• Keyboard shortcuts for audio player

A road trip in an electric vehicle doesn't have to be nerve-wracking anymore

Camila Domonoske

11 tips for a smooth EV road trip — without the range anxiety

Electric innovations past and present: The Hyundai Ioniq 6 that NPR took on a road trip stopped at the Thomas Edison Center at Menlo Park in Edison, N.J., on June 11. It’s the site of the world’s second-largest light bulb (that would be the one on top of the tower, at left) in honor of Thomas Edison. Amanda Andrade-Rhoades for NPR hide caption

Snacks, check. Playlist, check. Fully charged car — check?

Electric vehicles are central to automakers’ future. They’re key to climate advocates’ hopes. But most Americans remain leery of taking them on long road trips.

Electric cars have a road trip problem, even for the secretary of energy

And I get it. As NPR’s cars and energy correspondent, I’ve been on EV road trips where overcrowded and broken roadside chargers caused hassles and headaches. I’ve heard from EV enthusiasts who shrug off road trip angst, and from non-EV owners who say it’s a top reason they won’t go electric. And I’ve heard from auto executives and government officials who say improving the country’s charging infrastructure is a top priority.

So, is road trip charging getting any better?

Earlier this summer, photographer Amanda Andrade-Rhoades and I drove more than 1,000 miles, partly to try to answer that very question. What we found was a charging infrastructure at a point of flux. Cars are changing. Chargers are changing.

And things are getting better. Just not evenly.

The electric battery range is displayed on a Hyundai Ioniq's dashboard at NPR headquarters in Washington, D.C., the starting point for this trip. Amanda Andrade-Rhoades for NPR hide caption

Starting point: Washington, D.C.

Andrade-Rhoades and I met up at NPR’s headquarters in Washington, D.C., where we got into a borrowed 2024 Hyundai Ioniq 6 Limited with a fully charged battery. We plugged in a destination near Boston, agreed on our road trip playlist — that would be the highly bingeable podcast Normal Gossip — and hit the road, following the instructions from the car’s built-in navigation software.

We drove, riveted by the tales of other people’s drama, up the busy I-95 corridor.

I want to pause here to note: We spend way more time commuting than on long drives, and EVs handle daily driving with ease . Also, many households have multiple cars, so they might own an EV and never use it for road trips. And yet, Americans do love road trips — so addressing range anxiety matters.

We passed through Baltimore, Wilmington and Philadelphia, with a stop for lunch at Panera and a bit of sightseeing in New Jersey. Who could resist the allure of the world’s second-largest light bulb?

Photojournalist Amanda Andrade-Rhoades (left) and NPR correspondent Camila Domonoske take a selfie at the Thomas Edison Center at Menlo Park in Edison, N.J. An enormous light bulb on top is lit at night in honor of the famous inventor. Amanda Andrade-Rhoades for NPR hide caption

Road Stop 1: The Thomas Edison Memorial Tower at Menlo Park in New Jersey

The Ioniq’s built-in navigation software could identify when we needed to charge and what our options were. After 228 miles it recommended we stop. I vetoed its first suggestion for a charger — the station only had a single plug, which meant if someone beat us to it we could have a long wait.

So instead, we headed to the parking lot of a ShopRite — not quite as scenic as a giant light bulb, but hey, I wasn’t about to complain about a working charger where we needed one.

Domonoske charges up the EV in New Jersey. Amanda Andrade-Rhoades for NPR hide caption

Charge Stop 1: Bloomfield, N.J., 21 minutes

At the ShopRite’s EVgo station, we plugged the car (which we had named Serenity) into a charger (which EVgo had named Horatio).

Horatio opened less than two years ago. That's true for more than half of the non-Tesla fast chargers in the U.S., according to NPR's analysis of data from the Department of Energy . That's one sign of just how new America's fast-charging infrastructure is.

But "fast" is relative and varies by car. Next to us, MD Koyes Khan pulled up in his Toyota bZ4X. Fast-charging his EV from 20% to 80% takes “like, one hour … sometimes one and a half hours, depends on the weather,” he said.

And as an Uber and Lyft driver, he’s not making money while he waits to charge.

“It’s not good for us,” he says.

You asked, we answered: Your questions about electric vehicles

Different cars and different chargers have different maximum charge rates. Horatio, our charger, could charge at up to a blistering 350 kW. And the Ioniq 6 is a speedy-charging car; in certain configurations, it's the No. 1 fastest-charging EV on the market according to Edmunds and MotorTrend . (It’s a combination of a battery designed to handle the stress of a superfast charge, and an efficient car that gets more miles from a smaller battery.)

The result? We were back on the road in a hair over 20 minutes. That's longer than a gas stop, but way shorter than an hour. And just a few years ago, that kind of speed was mostly hypothetical.

Domonoske records an animatronic show at Stew Leonard’s, "The World’s Largest Dairy Store," in Norwalk, Conn. And what is a dairy store? Turns out it’s a lot like a grocery store — except a grocery store with animatronics, an ice cream stand and goats. Amanda Andrade-Rhoades for NPR hide caption

Goats canoodle at the petting zoo at Stew Leonard’s. Amanda Andrade-Rhoades for NPR hide caption

Road Stop 2: A dairy store in Norwalk, Conn.

When we had left D.C., the Ioniq 6 routed us toward Boston along a path that only required one charging stop. But as we got closer, the car said we’d need another one. Maybe it was our road stop detours (in addition to the light bulb, we’d stopped at “The World’s Largest Dairy Store” to get some ice cream and greet some goats). Maybe it was running the AC. Whatever the reason, it was clear we’d need a tad more juice.

Fortunately, there were plenty of options. We pulled into the back corner of a mall parking lot.

Beth Shapiro pays to charge her electric vehicle in Connecticut. Amanda Andrade-Rhoades for NPR hide caption

Charge Stop 2: Westfield Trumbull, Conn., 10 minutes

Are you getting the sense that an EV road trip is a tour of parking lots? That’s mostly true; while some companies are getting better about locating stations near amenities, many chargers have been plopped wherever there’s ample parking and easy access to electricity.

At this Electrify America station, we weren’t charging quite as quickly as at the EVgo, but we only needed a small top-up anyway. During our short stop, Beth Shapiro and her son Isaac Prusky pulled up in her Polestar 2.

She’s taken the car on several road trips and praised the experience. “People are so nice at these charging stations,” she said.

Their batteries hurt the environment, but EVs still beat gas cars. Here's why

The race is on to build EV battery-recycling plants in the U.S.

In fact, she only had one real complaint about driving an EV. “Sometimes I feel like I'm doing a good thing for the world, but then I worry because batteries are a problem,” she said. What exactly does she worry about? “Where this battery's going to go when it has no more useful life," she said, "and what it’s going to do to the universe.”

I told her we were on our way to a battery recycling company near Boston for a story about exactly that. We got back in the Ioniq to continue north.

Overnight charge: Residence Inn, Marlborough, Mass.

In our first day, we had traveled 436 miles over the course of 10 hours and charged for a total of half an hour. If I were traveling just for fun, I’d have sought out charging stops where we could also grab food for maximum efficiency — but since I was reporting, I wanted to use that time to talk to people.

But when it came to hotels, I planned this trip very much like I would a personal road trip, looking for hotels in our price range and along our route that offered chargers. Our Residence Inn had four plugs on the ChargePoint network, and while we slept, the Ioniq went from a 30% state of charge back to fully juiced up.

The next morning, we visited the EV battery recycling facility Ascend Elements in Westborough, Mass. ( Read all about it.) Then we hopped back on the road to return home.

An American flag is reflected in the window of an electric car. Amanda Andrade-Rhoades for NPR hide caption

Charge Stop 3: Pompton Lakes, N.J., 22 minutes

Our Day 2 drive required just one stop. We pulled into an Electrify America at the parking lot of a strip mall in this suburb of New York.

In the same parking lot was a Tesla Supercharger — with space for three times as many cars.

Tesla, love it or hate it , has been a transformative company in multiple ways. The Supercharger network was a very expensive bet that investing heavily in road trip chargers was key to getting car buyers to embrace EVs. And it worked. Road-tripping in a Tesla is better than in other EVs. The Supercharger network is the biggest and most reliable EV charger network in the country, without any serious rival.

I walked over to the Superchargers, where I chatted with driver Deepti Bhat. Turns out she’s no Tesla superfan. She had a long list of complaints about her car — the interior gets too hot, some parts get jammed — but none whatsoever about charging.

“Wherever I’ve stayed I’ve found charging nearby,” she says.

For many years only Tesla drivers could use those Superchargers. Now, in a major shift, other companies are embracing Tesla’s charging technology; in exchange, Tesla is gradually opening its network up to other users . Ford and Rivian got access first.

Other brands are still waiting, including Hyundai. So we were stuck at the Electrify America charging station. We got lucky — there was no wait. Jorge Nuñez, who charges at that station regularly, said he sometimes has to wait an hour for a slot.

I asked if he ever looked longingly over at all the empty Superchargers. “I do get jealous a little bit,” he said.

As Serenity charged, I chatted with local resident Agatha Hatzoglu, who pulled in next to Nuñez in her Volkswagen ID.4. She said she’s happy with the chargers in her corner of Jersey, but she prefers a gas car for trips to the Jersey Shore, where the chargers are fewer and farther between.

“I'm sure in the future it's going to be a lot better,” she says, “but I'm too old to wait for the future.”

She’s 76, and she looks great. I ask her for some skincare tips. Her advice? A plant-based diet. Oh, well.

A gap in the network near Allentown, Pa.

From Pompton Lakes we head south. But this time, instead of following the I-95 corridor and its abundant chargers, we turn slightly farther inland.

It’s probably common knowledge by this point that some parts of the country have a lot more chargers than others. California? Oodles. Wyoming? Oof.

The Northeast has lots of chargers, but it’s not just region by region that varies; within just a short drive, the charger map can look very different. That's why Hatzoglu liked driving an EV in some parts of New Jersey but not others. And that’s why coming south on I-78, barely an hour west of where we’d traveled the day before, we hit a stretch of interstate in central Pennsylvania where the closest charger was 50 miles away.

We had plenty of juice to make it through that stretch of highway without sweating it. But if we had unexpectedly needed a charge, it would have been a lot harder than it was in Connecticut.

“And not a single sign on the side of the road to indicate, ‘This is your last chance!’ ” Andrade-Rhoades pointed out. (In general, EV chargers and lack thereof aren’t advertised on highway signs — drivers need to watch apps or their car’s navigation system to know where to exit.)

The entrance to Hershey's Chocolate World in Hershey, Pa., is reflected in Domonoske's sunglasses. Amanda Andrade-Rhoades for NPR hide caption

People line up for a kitschy ride that shows the process of making Hershey’s chocolate in Hershey, Pa. Amanda Andrade-Rhoades for NPR hide caption

Road Stop 3: The Hershey's Chocolate World factory tour, Hershey, Pa.

In 2021, the federal government allocated billions of dollars for public EV chargers to plug gaps like these. And there are chargers planned, funded by that money, on that exact stretch of I-78.

But they’re not there yet. Pennsylvania is actually moving unusually fast to spend this money, with a few federally funded chargers already open and many others in the design phase. But unusually fast is still taking years. In most states, not a single federally-funded charger has opened.

Colton Brown, PennDOT’s EV guy, says there’s a lot of legwork that goes into opening these stations — from finding locations to striking deals with utilities — and the process is new for states. Charging stations aren’t a traditional infrastructure project.

A training program promised jobs working on EV chargers. The market hasn’t lived up

“Departments of Transportation, they're used to roads and bridges,” he points out. “It's a very different space to be in.”

After an overnight at the Best Western Plus in Hershey — where there was only a single charger, but fortunately it was all ours — we squeezed in one more road trip stop: the Hershey's Chocolate World factory tour.

I dropped Andrade-Rhoades off in D.C. and headed toward my home in Virginia’s Shenandoah Valley.

“Roughly 1 in 5 visits to a public charger ends in a failed charge event,” says Brent Gruber, who studies EVs for auto data company J.D. Power. Amanda Andrade-Rhoades for NPR hide caption

Charge Stop 4: Haymarket, Va., 6 minutes

We didn’t drain the battery much on our last — and shortest — day of driving. So the last charging stop took only six minutes. I added about 75 miles of range, enough to make it home to the Shenandoah Valley with battery to spare.

All told, we drove more than 1,000 miles. It took 2 ½ days. And charging? That took just under an hour, total. 

No question, you could refuel at gas stations much more quickly. On the other hand? That's significantly less time than we spent on food and bathroom breaks.

And, notably, every charger we visited worked.

EVs won over early adopters, but mainstream buyers aren't along for the ride yet

Your mileage may vary, of course. “Roughly 1 in 5 visits to a public charger ends in a failed charge event,” says Brent Gruber, who studies EVs for auto data company J.D. Power. That includes chargers that aren’t working, or have vandalized cords, or are so crowded that a driver gives up.

Gruber says we got lucky. But, he says, it wasn’t just luck.

“We are seeing signs of improvement across the board,” he says. “Speed, increased availability … the ease of charging is getting much better.”

My takeaway? The ease of road trip charging still depends on what you're driving, where you're driving, and how carefully you plan .

There’s still a long way to go before public charging infrastructure meets the needs of today’s EVs, let alone projections for the future. But the journey is underway.

• electric cars

Jaguar Is Going Electric. It Won't Sell Any Cars At Home For A Year

Jaguar is still committed to going all-electric. but while we wait for its new evs to launch, there's going to be a weird gap..

While other companies roll back their ambitious EV plans, Jaguar—a storied British brand that's been in need of fresh metal for some time now—is pressing forward. The company is planning to phase out its last gas model in many markets starting next year. There's only one problem: The EV replacements aren't here yet. So Jaguar will apparently go about a year without having any cars for sale in some markets.

That's according to a new report from Autocar , who sat down with Jaguar  Managing Director Rawdon Glove. The company has already announced that it is discontinuing all of its models except the F-Pace SUV, including its pioneering EV, the I-Pace .

But in some European markets and the UK, the F-Pace, too, will be discontinued by early 2025. Jaguar won't start delivering its first new EV until 2026, which means Jaguar retailers will have about a year to fill with no new cars in their showrooms. 

Get Fully Charged

Jaguar's Disappearing Lineup

Jaguar announced recently that it was canceling all of its products except for one. The F-Pace compact luxury crossover—which has long made up the lion's share of the brand's U.S. sales—is the only one left. Now, it's set to be discontinued in some markets, leaving Jaguar car-less in its home market.

Glove told Autocar  that "there will be a period where you will not be able to buy a Jaguar" in the U.K.

Glove said the dealers would focus on pre-owned cars and after-sales service during this time. I'd also imagine that, as in the U.S., many share their footprints with Land Rover dealers, which have been the focus of most franchises for quite a while as Jaguar has stalled out. It'll take a lot to kickstart the brand, but Jaguar has a lot planned. 

Jaguar's first EV model, the I-Pace, never really took off. It's being discontinued.

The company is looking to go upmarket in the EV era, and confirmed to Autocar that it will debut an all-electric GT car in December of this year. Jaguar is promising over 400 miles of range (on the generous WLTP cycle) and 575 hp, with a six-figure starting price. Autocar has the full report on the newer car, with a render that's worth checking out. 

It's also worth noting that Jaguar has had plans like this before, but the company has been mired in almost a decade of turmoil. 

Besides the uncertainty created by Brexit, Jaguar has dealt with management changes , a lack of new product, dimming sales and several strategy shifts since the late 2010s. Sales have dwindled from more than 180,000 in 2018 to under 67,000 in 2023. At one point, it was supposed to be debuting an electric XJ, a project that it supposedly spent half a billion British pounds on . Jaguar's latest set of managers seems committed to an all-electric future, but it's going to end up a kind of wholesale rebirth for the company.

What this latest plan means in the U.S. is unclear. Jaguar confirmed that the GT car would debut in the U.S. due to this market's importance to the brand. But it has not set an expiration date for the F-Pace here. I'd assume that, with our more lax emissions standard, the F-Pace will be fine to soldier on here until the new GT arrives in 2026. I'd assume Jaguar wouldn't want to have zero new cars in its showrooms. 

But I certainly never thought they'd have a dead year in their home market, and that's happening. I've reached out to Jaguar's U.S. PR team to see if they can share any information on the fate of the F-Pace. But even with it hanging on, Jaguar's all-electric reset can't come soon enough. The brand needs to be reinvented, and this will be its best shot.

Contact the author: [email protected] . 

Related Stories

• Share on Facebook
• Share on Twitter
• Share on LinkedIn
• Share on Flipboard
• Share on Reddit
• Share on WhatsApp
• Send to email

Find a vehicle

latest articles

• 7:15pm GMC Sierra EV: The Wait Is Nearly Over For Reservation Holders
• 3:45pm Volkswagen ID.4 Is More Affordable Than A Toyota Camry, Corolla
• 11:15am Ford's Affordable 'Skunkworks' EV: Everything We Know
• 6:20pm The Best EV Lease And Finance Deals In August 2024
• 4:30pm Donald Trump's Math On EV Chargers Is Way Off
• 4:00pm Tesla Now Offers A $5,000 Bundle With FSD And Unlimited Supercharging
• 3:40pm Why Are EV Sales 'Lagging'? Here Are Two Reasons.
• 3:31pm 2025 Ram 1500 REV: Everything We Know

About this article

• Aftermarket / Tuning
• Autonomous Vehicles
• Battery Tech
• Car Reviews
• First Drives
• Comparisons
• Everything We Know
• Test Drives
• Products & Services
• Buying Advice
• EV Education
• Aston Martin
• Automobili Pininfarina
• Faraday Future
• General Motors
• Lordstown Motors
• Mercedes-AMG
• Mercedes-Benz
• Nikola Motor
• Pininfarina
• Rolls-Royce
• Scout Motors
• Motorsport.com
• Motorsport.tv
• Rideapart.com
• Motorjobs.com
• Edition: USA / Global
• Édition: France
• Edizione: Italia
• Edição: Brasil
• Ausgabe: Deutschland
• EDİSYON: TÜRKİYE
• Edition: Argentina