BS-CDE: An Optimal Charging Strategy Model of BSSs for BSHTs Based on Improved NSGA-II Algorithm

被引:0
作者
Huang, Yulong [1 ]
Niu, Naiping [2 ]
Chen, Zehua [1 ]
Liu, Xiaofeng [1 ]
机构
[1] Taiyuan Univ Technol, Coll Comp Sci & Technol, Taiyuan 030024, Peoples R China
[2] Shanxi Keda Automat Control Co Ltd, Taiyuan 030006, Peoples R China
关键词
battery swapping station; heavy truck electrification; battery charging; multi-objective optimization; NSGA-II; ELECTRIC VEHICLES; BATTERY; OPERATION; STATION;
D O I
10.3390/pr13030755
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
HTs account for less than 7% of the automotive market in China, yet they contribute to more than 40% of the total carbon emissions from vehicles, with nitrogen oxide and particulate matter emissions exceeding 50% of the total vehicular emissions. BS for HTs has emerged as a crucial approach to reducing carbon emissions.As the number of BSHTs increases, the construction and operation of BSSs have become a pressing issue. This study focuses on the optimal charging strategy for BSSs by considering factors such as charging modes, charging durations, and real-time electricity prices. An optimal charging model, BS-CDE, is developed to formulate the operational cost problem of BSSs as a MOOP. By enhancing the traditional NSGA-II algorithm in aspects such as operators and parameter adjustments, the model is solved to obtain the optimal charging strategy, thereby reducing the operational costs of BSSs. Simulation results demonstrate that the proposed model effectively simulates the actual charging and battery-swapping processes for HTs. The results provide valuable guidance for the initial battery configuration and charging strategies of BSSs. Compared with traditional methods, the proposed model incorporates the actual operational scenarios of BSHTs while addressing multiple objectives during the charging process. Experimental results demonstrate that the proposed algorithm outperforms traditional methods, improving the HV and Sp metrics by 6.2% and 13.9%, respectively.
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页数:23
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