Chapter
Jul 2, 2019
Modeling of Charging Station Choice among EV Drivers Based on Prospect Theory
Authors: Yunshan Wang [email protected], Tianqi Jiang [email protected], Yangzi Lu [email protected], Zhaoqi Xu [email protected], Yan Xia [email protected], and Zhiyuan Liu [email protected]Author Affiliations
Publication: CICTP 2019
Abstract
This study presents a prospect theory model, focusing on electric vehicle (EV) drivers’ choice from a set of charging stations. The research consists of three parts including driver classification, model construction and model validation. Based on the state of charging (SOC) and charging time, the EV drivers are divided into three categories and these three types have different risk propensity which affects drivers’ choices. The prospect value is calculated according to the drivers’ categories, the detour distance, charging cost, and time cost. The proposed model is validated by a small scale case study in Shanghai. A useful method to determine the reasonable alternative charging stations is also provided to avoid time-consuming searching among all stations in Shanghai. The parameters are also calibrated according to the large scale case study.
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© 2019 American Society of Civil Engineers.
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Published online: Jul 2, 2019
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School of Transportation, Southeast Univ., Nanjing, China; Jiangsu Provincial Key Laboratory of Networked Collective Intelligence, Nanjing, Jiangsu 211189, China. E-mail: [email protected]
School of Transportation, Southeast Univ., Nanjing, Jiangsu 211189, China. E-mail: [email protected]
School of Transportation, Southeast Univ., Nanjing, Jiangsu 211189, China. E-mail: [email protected]
School of Transportation, Southeast Univ., Nanjing, Jiangsu 211189, China. E-mail: [email protected]
School of Transportation, Southeast Univ., Nanjing, Jiangsu 211189, China. E-mail: [email protected]
School of Transportation, Southeast Univ., Nanjing, Jiangsu 211189, China. E-mail: [email protected]
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