基于Pareto原理的HEV能量控制参数NSGA-Ⅱ多目标优化的研究

A Research on NSGA-Ⅱ Multi-objective Optimization for HEV Energy Management Parameters Based on Pareto Principle

以某款并联混合动力汽车为对象,选取8个能量控制参数作为燃油经济性和排放性综合优化参数,提出基于Pareto原理的改进型NSGA-Ⅱ多目标优化算法,并进行仿真优化。结果表明:优化后燃油消耗率最大降低了11.29%,排放物综合指标最大下降8.78%,其中CO排放的优化效果最显著,下降了24.2%;SOC平衡的误差在0.5%以内,满足约束条件,发动机与电机工作点的效率分布明显改进;同时相比传统加权等单目标优化法,所提出的算法能同时得到多组优化解,为能量管理前期设计提供了更多的选择空间。

With a parallel hybrid electric vehicle as objective,eight energy management parameters are chosen as comprehensive optimization parameters for fuel economy and emission performance,an improved NSGA-Ⅱ multi-objective optimization algorithm based on Pareto principle is proposed,with a simulation optimization conducted. The results show that after optimization,the fuel consumption decreases by 11. 29% at most,the overall emission indicator lowers by 8. 78% at most,in which the optimization effectiveness of CO emission is most significant,reducing by 24. 2%,the SOC deviation is within 0. 5%,meeting its constraint condition,and the distribution of working points and their efficiency for both engine and motor are obviously improved. In addition,compared with single objective optimization algorithms including traditional weighting scheme,the algorithm proposed can obtain much more optimized solution sets,hence providing much more options to choose in preliminary design of HEV energy management.