Optimal path planning method of electric vehicles considering power supply

Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use...

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Bibliographic Details
Published in:Journal of Central South University 2022, Vol.29 (1), p.331-345
Main Authors: Guo, Dong, Li, Chao-chao, Yan, Wei, Hao, Yu-jiao, Xu, Yi, Wang, Yu-qiong, Zhou, Ying-chao, Wen-juan, E., Zhang, Tong-qing, Gao, Xing-bang, Tan, Xiao-chuan
Format: Article
Language:English
Subjects:
Algorithms
Charging
Driving
Electric vehicles
Energy consumption
Engineering
Metallic Materials
Multiple objective analysis
Optimization
Path planning
Power supply
Road conditions
Route planning
Shortest-path problems
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Summary:Because of the limitations of electric vehicle (EV) battery technology and relevant supporting facilities, there is a great risk of breakdown of EVs during driving. The resulting driver “range anxiety” greatly affects the travel quality of EVs. These limitations should be overcome to promote the use of EVs. In this study, a method for travel path planning considering EV power supply was developed. First, based on real-time road conditions, a dynamic energy model of EVs was established considering the driving energy and accessory energy. Second, a multi-objective travel path planning model of EVs was constructed considering the power supply, taking the distance, time, energy, and charging cost as the optimization objectives. Finally, taking the actual traffic network of 15 km×15 km area in a city as the research object, the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm. The simulation results show that compared with the traditional route planning method, the total distance in the proposed optimal route planning method increased by 1.18%, but the energy consumption, charging cost, and driving time decreased by 11.62%, 41.26% and 11.00%, respectively, thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.
ISSN:2095-2899
2227-5223
DOI:10.1007/s11771-022-4924-x