Optimal Capacity Model for Battery Swapping Station of Electric Taxis: A Case Study in Chengdu

Siyu Xie, Guangyan Wang, Yiyi Zhang, Bo Li () and Junhui Zhao ()
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Siyu Xie: School of Electrical Engineering, Guangxi University, Nanning 530004, China
Guangyan Wang: Liaocheng Power Supply Company Dongchang Power Supply Center, STATE GRID Corporation of China, Liaocheng 252000, China
Yiyi Zhang: School of Electrical Engineering, Guangxi University, Nanning 530004, China
Bo Li: School of Electrical Engineering, Guangxi University, Nanning 530004, China
Junhui Zhao: Eversource Energy, Berlin, CT 06037, USA

Sustainability, 2024, vol. 16, issue 4, 1-13

Abstract: Battery swapping station (BSS) technology can provide electric taxis (ETs) with more economical and high-efficiency operating services. However, the battery-swapping market needs to be more organized due to unpredictable swapping periods for ETs, resulting in more requirements for batteries of BSSs needing multiple batteries simultaneously. To address these challenges, this paper first analyzed two operation patterns of taxis to estimate the demand for swapping ETs. Then, an optimal capacity model of BSS is proposed to optimize the battery capacity of BSSs to meet the swapping demand of ETs. Finally, a genetic algorithm (GA) is utilized to solve the proposed model. The real operating data of taxis with GPS routes in Chengdu city are used as a case study to validate the proposed method. The results show that the proposed method could obtain the optimal battery capacity of a BSS and improve the economic benefits of BSSs.

Keywords: battery swapping stations; electric taxis; optimal capacity; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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