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Optimal battery electric vehicles range: A study considering heterogeneous travel patterns, charging behaviors, and access to charging infrastructure

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  • Zhou, Yue
  • Wen, Ruoxi
  • Wang, Hewu
  • Cai, Hua

Abstract

The choice of battery range (all-electric driving range) for battery electric vehicles (BEVs) is an important issue for both BEV adopters and BEV makers. This paper proposes a model to identify the minimum BEV battery range that can satisfy given travel demands, considering the opportunities to charge at existing public charging stations and the uncertainties in charging decision making. We conducted a stated preference survey to study the charging decision making and analyzed the data using the Latent Class model to generate the model coefficients for charging decisions making. The proposed approach can better identify the needed battery range than the often-used simplified charging rules. We applied the model to a case study of Beijing to evaluate the needed battery range for taxis and private vehicles. For taxis, BEVs with 220-mile battery range are able to satisfy the travel demands for about 90% of the drivers. For private vehicles, a 300-mile range is needed to cover the travel demands of 90% of the drivers, while a 100-mile range battery is able to satisfy the need for 80% of the private drivers. Simplified charging rules tend to underestimate the range needs for taxis but overestimate the range needs for private vehicles.

Suggested Citation

  • Zhou, Yue & Wen, Ruoxi & Wang, Hewu & Cai, Hua, 2020. "Optimal battery electric vehicles range: A study considering heterogeneous travel patterns, charging behaviors, and access to charging infrastructure," Energy, Elsevier, vol. 197(C).
    • Handle: RePEc:eee:energy:v:197:y:2020:i:c:s0360544220300529
    DOI: 10.1016/j.energy.2020.116945
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    1. Gao, Zhiming & Lin, Zhenhong & LaClair, Tim J. & Liu, Changzheng & Li, Jan-Mou & Birky, Alicia K. & Ward, Jacob, 2017. "Battery capacity and recharging needs for electric buses in city transit service," Energy, Elsevier, vol. 122(C), pages 588-600.
    2. Brett Williams & Elliot Martin & Timothy Lipman & Daniel Kammen, 2011. "Plug-in-Hybrid Vehicle Use, Energy Consumption, and Greenhouse Emissions: An Analysis of Household Vehicle Placements in Northern California," Energies, MDPI, vol. 4(3), pages 1-23, March.
    3. Xu, Min & Meng, Qiang & Liu, Kai & Yamamoto, Toshiyuki, 2017. "Joint charging mode and location choice model for battery electric vehicle users," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 68-86.
    4. Shi, Xiao & Pan, Jian & Wang, Hewu & Cai, Hua, 2019. "Battery electric vehicles: What is the minimum range required?," Energy, Elsevier, vol. 166(C), pages 352-358.
    5. Khan, Mobashwir & Kockelman, Kara M., 2012. "Predicting the market potential of plug-in electric vehicles using multiday GPS data," Energy Policy, Elsevier, vol. 46(C), pages 225-233.
    6. Björnsson, Lars-Henrik & Karlsson, Sten, 2015. "Plug-in hybrid electric vehicles: How individual movement patterns affect battery requirements, the potential to replace conventional fuels, and economic viability," Applied Energy, Elsevier, vol. 143(C), pages 336-347.
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    8. Pareschi, Giacomo & Küng, Lukas & Georges, Gil & Boulouchos, Konstantinos, 2020. "Are travel surveys a good basis for EV models? Validation of simulated charging profiles against empirical data," Applied Energy, Elsevier, vol. 275(C).
    9. Subhaditya Shom & Kevin James & Mahmoud Alahmad, 2022. "Understanding the Correlation of Demographic Features with BEV Uptake at the Local Level in the United States," Sustainability, MDPI, vol. 14(9), pages 1-21, April.
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    11. Aritra Ghosh, 2020. "Possibilities and Challenges for the Inclusion of the Electric Vehicle (EV) to Reduce the Carbon Footprint in the Transport Sector: A Review," Energies, MDPI, vol. 13(10), pages 1-22, May.
    12. Sprei, Frances & Kempton, Willett, 2024. "Mental models guide electric vehicle charging," Energy, Elsevier, vol. 292(C).
    13. Bassem Haidar & Pascal da Costa & Jan Lepoutre & Fabrice Vidal, 2020. "Which combination of battery capacity and charging power for battery electric vehicles: urban versus rural French case studies," Post-Print hal-03071656, HAL.
    14. Karol Tucki & Olga Orynycz & Mateusz Mitoraj-Wojtanek, 2020. "Perspectives for Mitigation of CO 2 Emission due to Development of Electromobility in Several Countries," Energies, MDPI, vol. 13(16), pages 1-24, August.
    15. Xiangyu Luo & Rui Qiu, 2020. "Electric Vehicle Charging Station Location towards Sustainable Cities," IJERPH, MDPI, vol. 17(8), pages 1-22, April.
    16. Eva Jaderná & Radka Hakl & Lada Honzáková & Petr Dolejší, 2026. "Acceptance of electromobility: who is buying electric cars?," Future Business Journal, Springer, vol. 12(1), pages 1-13, December.
    17. Zhao, Yinan & Wang, Fang & Zhang, Shaojun & Wu, Ye & Hao, Jiming, 2025. "Decarbonization potential of Chinese PHEVs: Impact of increased battery range, power mix, and usage patterns," Energy, Elsevier, vol. 331(C).
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    21. Zhu, Xiaoxi & Chiong, Raymond & Wang, Miaomiao & Liu, Kai & Ren, Minglun, 2021. "Is carbon regulation better than cash subsidy? The case of new energy vehicles," Transportation Research Part A: Policy and Practice, Elsevier, vol. 146(C), pages 170-192.
    22. Veronika Štekerová & Martin Kotek & Veronika Hartová, 2020. "Comparison of two electric vehicles in terms of real range in different types of operations," Research in Agricultural Engineering, Czech Academy of Agricultural Sciences, vol. 66(4), pages 140-145.
    23. Aixin Yang & Guiqing Zhang & Chenlu Tian & Wei Peng & Yechun Liu, 2024. "Charging Behavior Portrait of Electric Vehicle Users Based on Fuzzy C-Means Clustering Algorithm," Energies, MDPI, vol. 17(7), pages 1-26, March.

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