基于强度帕累托进化算法的复合电源参数优化

Parameter optimization of hybrid energy storage system based on strength Pareto evolutionary algorithm

采用动力锂离子电池加超级电容的复合电源系统,可以提高整车经济性并延缓电池的老化,针对复合电源系统参数设计优化问题,提出了一种基于多目标优化算法的复合电源系统参数设计方法。首先,基于对复合电源系统的研究现状分析,确定其构型及能量管理策略,构建了系统模型;然后,以系统成本和日均能耗为评价指标建立多目标优化模型,再依据整车需求的性能指标确定参数优化区间;采用强度帕累托进化算法(SPEA2)设计了复合电源系统的参数优化流程并进行了参数优化和性能分析,同时将所提出的SPEA2与快速非支配排序遗传算法(NSGA-Ⅱ)进行了对比分析。结果表明,SPEA2优化结果有效地提高了动力电池的性能,证明了所提出的SPEA2优化方法的可行性与有效性。

The hybrid energy storage system consisting of lithium-ion power battery and supercapacitor can improve the vehicle economy and delay the aging of the battery. Aiming at the parameter design optimization of the hybrid energy storage system, a parameter design method of the hybrid energy storage system based on multi-objective optimization algorithm was proposed. Firstly, based on the analysis of the research of the hybrid energy storage system, the topology and energy management strategy were determined, and the system model was built. Then, the multi-objective optimization model was established with the system cost and daily energy consumption as the evaluation indexes, and the parameter optimization ranges was determined according to the performance of the vehicle. The strength Pareto evolutionary algorithm(SPEA2) was used to design the parameter optimization process of the hybrid energy storage system and the parameter optimization and performance analysis were carried out.Meanwhile, the proposed SPEA2 was compared with the fast non-dominated sorting genetic algorithm(NSGA-Ⅱ). The results show that the SPEA2 optimization results effectively improve the performance of power batteries, which proves the feasibility and effectiveness of the proposed SPEA2 optimization method.