基于改进NSGA-Ⅱ的电动汽车复合电源多目标参数优化

Multi-objective parameter optimization of electric car composite power supply based on improved NSGA-Ⅱalgorithm

为提高电动汽车复合电源利用效率,设计一种基于改进NSGA-Ⅱ算法的电动汽车复合电源参数优化模型。分析电动汽车电池衰减特征与日均运行成本,改进NSGA-Ⅱ算法,对优化目标求解得到Pareto解集。仿真实验工况研究结果表明:在控制电动汽车的运行成本与电池衰减率方面存在互相制约的限制,优化Pareto解配置,控制电动汽车日均成本为重点目标。对比等效结果可知,优化配置后降低动力电池日均性能衰减程度约为32%。按照优化配置动力电池数量比等效计算配置数更多,达到更大的荷电状态(SOC)终值与均值,确保动力电池达到里程与最大车速运行状态下获得更高峰值功率。该研究有效控制动力电池发生深度放电过程,使电动汽车达到更高效率。

In order to improve the utilization efficiency of electric car composite power supply,a parameter optimization model of electric car composite power supply based on improved NSGA-Ⅱalgorithm was designed.The characteristics of electric car battery attenuation and daily operating cost were analyzed.Pareto solution set was obtained by improved NSGA-Ⅱalgorithm to solve and calculate the optimization objective,and then the configuration parameters of composite power supply under corresponding working conditions were obtained.The results of simulation experiments show that there are mutual constraints in the control of electric car operating cost and battery attenuation rate,and the optimization of Pareto solution configuration is aimed at controlling electric car daily cost.Compared with the equivalent calculation results,the average daily performance attenuation of the power battery can be reduced by about 32%after optimized configuration.According to the optimized configuration,the number of power batteries is more than the equivalent configuration,and the final value and average value of SOC are larger,ensuring that the power battery can obtain higher peak power when it reaches the mileage and maximum speed.This research can effectively control the deep discharge process of the power battery and make the electric car achieve higher efficiency.