An Optimal Battery Charging Algorithm in Electric Vehicle-Assisted Battery Swapping Environments
- Authors
- Ko, Haneul; Pack, Sangheon; Leung, Victor C. M.
- Issue Date
- 5월-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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Collections - Graduate School > Department of Computer and Information Science > 1. Journal Articles
- College of Engineering > School of Electrical Engineering > 1. Journal Articles
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