Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles

Currently, the layout planning of power exchange facilities in urban areas is not perfect, which cannot effectively meet the power exchange demand of urban operating vehicles and restricts the operation of urban operating vehicles. The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. The results show that the MLP-NSGA-II joint algorithm has the lowest cost of optimizing the location of switching stations. The results show that the MLP-NSGA-II algorithm improves the convergence efficiency by about 30.23%, and the service coverage of the optimal solution reaches 94.30%; the service utilization rate is 85.35%, which is 6.25% and 19.69% higher than that of the GA and DPC, respectively. The research content of the article can provide a design basis for the future configuration of the number and location of power exchange stations in urban areas.

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Publication Details

Journal
World Electric Vehicle Journal
Published
2025-06-16
DOI
https://doi.org/10.3390/wevj16060332
Citations
2
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
1.46

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article

Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles

Haowen Li, Tengfei Ma, Bin Zhou, Pengcheng Ma et al.
2 citations
World Electric Vehicle Journal
Electric Vehicles and Infrastructure
1.46
article

Research on Location Planning of Battery Swap Stations for Operating Electric Vehicles

Haowen Li, Tengfei Ma, Bin Zhou, Pengcheng Ma, Dong Guo, Shuai Zhang, Wan-zhne Shao
article en
2 citations

Abstract

Currently, the layout planning of power exchange facilities in urban areas is not perfect, which cannot effectively meet the power exchange demand of urban operating vehicles and restricts the operation of urban operating vehicles. The article proposes a vehicle power exchange demand-oriented power exchange station siting planning scheme to meet the rapid replenishment demand of operating vehicles in urban areas. The spatial and temporal distribution of power exchange demand is predicted by considering the operation law, driving law, and charging decision of drivers; the candidate sites of power exchange stations are determined based on the data of power exchange demand; the optimization model of the site selection of power exchange stations with the lowest loss time of vehicle power exchange and the lowest cost of the planning and construction of power exchange stations is established and solved by using the joint algorithm of MLP-NSGA-II; and the optimization model is compared with the traditional genetic algorithm (GA) and the Density Peak. The results show that the MLP-NSGA-II joint algorithm has the lowest cost of optimizing the location of switching stations. The results show that the MLP-NSGA-II algorithm improves the convergence efficiency by about 30.23%, and the service coverage of the optimal solution reaches 94.30%; the service utilization rate is 85.35%, which is 6.25% and 19.69% higher than that of the GA and DPC, respectively. The research content of the article can provide a design basis for the future configuration of the number and location of power exchange stations in urban areas.

World Electric Vehicle JournalVol. 16(6)
Shandong University of Technology (CN)
National Natural Science Foundation of China, Shandong University of Technology and Zibo City Integration Development Project
Openalex Percentile: Top 17%
Electric Vehicles and Infrastructure
1.46
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