A geometry-based algorithm to provide guidance for electric vehicle charging. (August 2018)

• Record Type: Journal Article
• Authors: Wang, Yongxing; Bi, Jun; Zhao, Xiaomei; Guan, Wei
• Is Part Of: Transportation research. Volume 63(2018)
• Page Start: 890
• Page End: 906
• Publication Date: 2018-08
• Subjects: Electric vehicle -- Smart charging service -- Charging guidance -- Geometry-based algorithm -- Charging request; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2018.07.017
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: A geometry-based algorithm is proposed to recommend suitable charging stations to electric vehicles. Travel distance and driving direction characteristic are considered in the algorithm. Geographic research findings and geometric approaches are applied to design the algorithm. Abstract: Electric vehicles (EVs) have been regarded as effective options for solving the environmental and energy problems in the field of transportation. However, given the limited driving range and insufficient charging stations, searching and selecting charging stations is an important issue for EV drivers during trips. A smart charging service should be developed to help address the charging issue of EV drivers, and a practical algorithm for charging guidance is required to realise it. This study aims to design a geometry-based algorithm for charging guidance that can be effectively applied in the smart charging service. Geographic research findings and geometric approaches are applied to design the algorithm. The algorithm is practical because it is based on the information from drivers' charging requests, and its total number of calculations is significantly less than that of the conventional shortest-first algorithm. The algorithm is effective because it considers the consistency of direction trend between the charging route and the destination in addition to the travel distance, which conforms to the travel demands of EV drivers. Moreover, simulation examples are presented to demonstrate the proposed algorithm. Results of the proposed algorithm are compared with those of the other two algorithms, which show that the proposed algorithm can obtain a better selection of charging stations for EV drivers from the perspective of entire travel chains and take a shorter computational time.