4.7 Article

Electric vehicle drivers' charging behavior analysis considering heterogeneity and satisfaction

期刊

JOURNAL OF CLEANER PRODUCTION
卷 286, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2020.124982

关键词

Electric vehicles; Charging choice behavior; Binary logit model; Latent class model

资金

  1. National Key R&D Program of China [2018YFB1601300]

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This study analyzed the factors influencing EV drivers' charging choices and proposed charging influence models and choice behavior models. Results revealed two decision-making patterns among EV drivers: service-concerned and pragmatic-concerned, suggesting the need for reliable high-quality charging services to attract more EV drivers.
Electric vehicles (EVs) have been developed rapidly in recent years in China, but a further promotion of EVs is hindered by the unreasonable deployment of facilities. Therefore, a deep understanding of EV drivers' charging behavior is viewed to be helpful to a more suitable deployment of new chargers. In this paper, charging influence factors are analyzed, and logit-based models for charging choice behaviors are proposed. First, a web-based stated preference survey is designed to obtain the data of EV drivers' charging choice preference. Second, binary logit models are developed using the survey data, with vehicle attributes, destination activity, and subsequent travel information as influence factors. Especially, the satisfaction of charging facilities reviewed by previous users and drivers' risk attitudes are also introduced to analyze charging choice preference. Third, latent class models are proposed to further taste the heterogeneity of EV drivers' charging decision strategies. The results reveal two classes of decision making patterns among our sample population: (1) service concerned, which are the majority of the respondents who value the satisfaction and queue of charging station, characterized with younger age, richer driving experience and higher income, and (2) pragmatic concerned, those who weight multiple factors, such as excess range, parking time, and charging fee. It suggests that the improvement of charging service levels, such as providing reliable and high-quality charging service, is necessary for operators to attract more EV drivers. (c) 2020 Elsevier Ltd. All rights reserved.

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