Stochastic frontier analysis of excess access to mid-trip battery electric vehicle fast charging |
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| Institution: | 1. Department of Civil Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;2. EcoTopia Science Institute, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;3. Graduate School of Environmental Studies, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;1. School of Transportation and Logistics, Dalian University of Technology, No. 2 Linggong Road, Ganjingzi District, Dalian 116024, China;2. Institute of Materials and Systems for Sustainability, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;3. Institute of Innovation for Future Society, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan;1. Dept. of Electronic and Electrical Engineering, University of Strathclyde, Glasgow, UK;2. DTU Elektro, Denmark Technical University, Lyngby, Denmark;1. School of Industrial Engineering, Purdue University, West Lafayette, IN, 47907, United States;2. State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, 100084, China;3. Environmental and Ecological Engineering, Purdue University, West Lafayette, IN, 47907, United States;1. Department of Engineering Science, University of Oxford, OX1 3PJ, UK;2. Department of Civil, Environmental, and Architectural Engineering, University of Colorado, Boulder, CO 80301, USA;3. School of Engineering, University of Edinburgh, EH9 3FB, UK;1. Department of Civil and Environmental Engineering, University of Michigan, Ann Arbor, 48107, United States;2. Division of Engineering and Computer Science, NYU Shanghai, Shanghai 200122, China;3. Center for Data Science and Artificial Intelligence, NYU Shanghai, Shanghai 200122, China |
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| Abstract: | This study aims to explore how factors including charging infrastructure and battery technology associate the way people currently charge their battery electric vehicles, as well as to explore whether good use of battery capacity can be encouraged. Using a stochastic frontier model applied to panel data obtained in a field trial on battery electric vehicle usage in Japan, the remaining charge when mid-trip fast charging begins is treated as a dependent variable. The estimation results obtained using four models, for commercial and private vehicles, respectively, on working and non-working days, show that remaining charge is associated with number of charging stations, familiarity with charging stations, usage of air-conditioning or heater, battery capacity, number of trips, Vehicle Miles of Travel, paid charging. However, the associated factors are not identical for the four models. In general, EVs with high-capacity batteries are initiated at higher remaining charge, and so are the mid-trip fast charging events in the latter period of this trial. The estimation results also show that there are great opportunities to encourage more efficient charging behavior. It appears that the stochastic frontier modeling method is an effective way to model the remaining charge at which fast-charging should be initiated, since it incorporates trip and vehicle characteristics into the estimation process to some extent. |
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| Keywords: | Battery electric vehicle Field trial Fast charging behavior Mid-trip State of charge Stochastic frontier model |
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