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Title: Mitigate the range anxiety : siting battery charging stations for electric vehicle drivers
Authors: Xu, M 
Yang, H
Wang, SA 
Issue Date: May-2020
Source: Transportation research. Part C, Emerging technologies, May 2020, v. 114, p. 164-188
Abstract: This study addresses the location problem of electric vehicle charging stations considering drivers’ range anxiety and path deviation. The problem is to determine the optimal locations of EV charging stations in a network under a limited budget that minimize the accumulated range anxiety of concerned travelers over the entire trips. A compact mixed-integer nonlinear programming model is first developed for the problem without resorting to the path and detailed charging pattern pre-generation. After examining the convexity of the model, we propose an efficient outer-approximation method to obtain the ε-optimal solution to the model. The model is then extended to incorporate the charging impedance, e.g., the charging time and cost. Numerical experiments in a 25-node benchmark network and a real-life Texas highway network demonstrate the efficacy of the proposed models and solution method and analyze the impact of the battery capacity, path deviation tolerance, budget and the subset of OD pairs on the optimal solution and the performance of the system.
Keywords: EV charging station location
Range anxiety
Compact formulation
Outer-approximation algorithm
Path deviation
Publisher: Pergamon Press
Journal: Transportation research. Part C, Emerging technologies 
ISSN: 0968-090X
DOI: 10.1016/j.trc.2020.02.001
Rights: ©2020 Elsevier Ltd. All rights reserved.
© 2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license
The following publication Xu, M., Yang, H., & Wang, S. (2020). Mitigate the range anxiety: Siting battery charging stations for electric vehicle drivers. Transportation Research Part C: Emerging Technologies, 114, 164-188 is available at
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