Dominant charging location choice of commuters and non-commuters: a big data approach

Xiong Yang (), Chengxiang Zhuge (), Chunfu Shao (), Runhang Guo (), Andrew Tin Chak Wong (), Xiaoyu Zhang (), Mingdong Sun (), Pinxi Wang () and Shiqi Wang ()
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Xiong Yang: The Hong Kong Polytechnic University
Chengxiang Zhuge: The Hong Kong Polytechnic University
Chunfu Shao: Beijing Jiaotong University
Runhang Guo: The Hong Kong Polytechnic University
Andrew Tin Chak Wong: The Hong Kong Polytechnic University
Xiaoyu Zhang: Beijing Jiaotong University
Mingdong Sun: Beijing Jiaotong University
Pinxi Wang: Beijing Transport Institute
Shiqi Wang: The Hong Kong Polytechnic University

Transportation, 2025, vol. 52, issue 2, No 3, 439-466

Abstract: Abstract This paper is focused on electric vehicle (EV) users’ dominant charging locations, where they get their EVs recharged more frequently. We particularly compared the dominant charging location choice of commuters and non-commuters using a unique one-month trajectory dataset collected from 76,774 actual private EVs in Beijing in January 2018. Specifically, we first grouped EV users for both commuters and non-commuters according to their dominant charging locations and then characterized and compared their charging patterns. Further, we associated the dominant charging location choice of EV users with their characteristics using a mixed logistic regression model. The results suggested that over 50% of the EV users were the Home Dominated users with most charging events occurring around home. Further, there were significant differences in charging patterns of EV users from different groups by dominant charging location, and also between commuters and non-commuters. Commuters tended to have a lower SOC than non-commuters when they got their EVs recharged. Moreover, the dominant charging location choice of EV users was significantly associated with their characteristics, including charging opportunities available and mobility patterns, and the association is different for commuters and non-commuters. The results are expected to be useful for deploying charging infrastructure.

Keywords: Electric vehicle; Commuters; Dominant charging location; Trajectory data; Mixed logistic regression model (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11116-023-10427-8

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