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An Optimal Battery Charging Algorithm in Electric Vehicle-Assisted Battery Swapping Environments

Authors
Ko, HaneulPack, SangheonLeung, Victor C. M.
Issue Date
May-2022
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Keywords
Batteries; Quality of service; Schedules; Markov processes; Delays; Heuristic algorithms; Cascading style sheets; Battery swapping; battery swapping station (BSS); battery charging algorithm; electric vehicle (EV); constraint Markov decision process (CMDP)
Citation
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, v.23, no.5, pp.3985 - 3994
Indexed
SCIE
SCOPUS
Journal Title
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
Volume
23
Number
5
Start Page
3985
End Page
3994
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/141762
DOI
10.1109/TITS.2020.3038274
ISSN
1524-9050
Abstract
In battery swapping environments, electric vehicles (EVs) can play roles as battery providers as well as consumers. In this paper, we propose an optimal battery charging algorithm (OBCA) where a battery swapping station (BSS) charges batteries in its storage with the consideration of the profile of the electricity price and the arrival rates of EVs. To maximize the net profit of BSS while maintaining the battery changing probability above a certain level (i.e., maintaining high quality of service (QoS) of BSS), we formulate a constraint Markov decision process (CMDP) problem and the optimal charging schedule for batteries in BSS is obtained by a linear programming (LP). Evaluation results demonstrate that OBCA with the optimal policy can improve the net profit of BSS up to 418% compared to an electric price-aware scheme while maintaining high QoS of BSS.
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College of Engineering (School of Electrical Engineering)
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