A Novel Power Distribution Strategy and Its Online Implementation for Hybrid Energy Storage Systems of Electric Vehicles

被引:4
作者
Jiang, Nanmei [1 ]
Wang, Xuemei [1 ]
Kang, Longyun [1 ]
机构
[1] South China Univ Technol, Sch Elect Power, Guangzhou 510641, Peoples R China
关键词
power distribution; energy storage; vehicles; pattern recognition; optimal control; MODEL-PREDICTIVE CONTROL; MANAGEMENT STRATEGY; BATTERY; LIFE; OPTIMIZATION; TIME;
D O I
10.3390/electronics12020301
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Hybrid energy storage systems (HESS) composed of a battery and ultracapacitor (UC) provide a feasible solution to the economy of electric vehicles (EVs). To fully exploit the potential of HESSs, a power distribution strategy that can split power between the battery and UC in HESSs plays an important role. Therefore, a novel power distribution strategy and its online application are proposed in this paper. First, a new and simple power distribution model of HESSs is proposed, and the model parameters are optimized offline through particle swarm optimization (PSO). Then, a driving condition recognizer based on a neural network is introduced, and the online application of the strategy is realized by combining offline global optimization and online recognition. Compared with the traditional rule-based strategy, the strategy proposed reduces the average fluctuation of the battery current by 52.53% and the average amplitude of the battery current by 11.51%. Meanwhile, it can be seen from the results that the strategy proposed is very close to the offline PSO-based strategy proposed and exhibits good performance under all driving cycles.
引用
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页数:16
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