Distributed approach for temporal: spatial charging coordination of plug-in electric taxi fleet

Zaiyue YANG*, Tianci GUO, Pengcheng YOU, Yunhe HOU, S. Joe QIN

*Corresponding author for this work

Research output: Journal PublicationsJournal Article (refereed)peer-review

26 Citations (Scopus)


This paper considers a city with a large fleet of plug-in electric taxis (PETs) and studies the charging coordination problem of the fleet. The goal is to reduce charging cost for each PET, defined as the loss of service income caused by charging, by wisely choosing when and where to charge. Considering the fact that the fleet can contain thousands of autonomous PETs, this problem is approached in a distributed way. In detail, a two-stage decision process is designed for each PET in an online fashion upon receiving real-time information. In the first stage, a thresholding method is proposed to assist a PET driver in choosing a proper time slot for charging, with comprehensive consideration of state of charge of PET, time varying income, and queuing status at charging stations (CSs). In the second stage, a game-theoretical approach is devised for PETs to select CSs, so that the traveling and queuing time of each PET can be reduced with fairness. Extensive numerical simulations illustrate the following threefold benefits of the proposed approach: it can effectively reduce the charging cost for PETs, enhance Utilization ratio for CSs, and also flatten Unevenness of charging request for power grid.

Original languageEnglish
Article number8521690
Pages (from-to)3185-3195
Number of pages11
JournalIEEE Transactions on Industrial Informatics
Issue number6
Publication statusPublished - Jun 2019
Externally publishedYes

Bibliographical note

This work was supported in part by the Natural Science Foundation of China under Grant 61873118 and in part by the Shenzhen Committee on Science and Innovations under Grant GJHZ20180411143603361 and Grant 20160207. Paper no. TII-18-1161.


  • Backward induction
  • game-theoretical approach
  • plug-in electric taxi (PET)
  • spatial selection
  • temporal scheduling


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