基于NSGA-Ⅱ算法的复合电源混合动力系统参数匹配优化

Optimization of Parameter Matching of Hybrid Power System for HEV based on NSGA-Ⅱ Algorithm

针对复合电源混合动力系统传统参数优化算法目标比较单一的缺陷,以燃油经济性、排放性和舒适性作为多目标参数优化对象,以整车动力性指标作为约束条件,提出NSGA-Ⅱ多目标参数优化算法。优化结果表明:在满足动力性指标和车速跟随基本吻合的情况下,优化后的燃油经济性指标平均提高了5.51%,排放性指标平均提高了14.86%,舒适性指标达到了使人感到舒适的程度,蓄电池的最高充放电电流降低了一半。而且获得的一系列分布均匀全局最优解,优化结果比较满意,验证了提出的参数匹配优化算法的准确性和适用性。

Aiming at the defects of single target for traditional parameter optimization on hybrid power for hybrid electric vehicle（ HEV）,the fuel economy,emission and riding comfort are as the multi-objectives optimization object,and taking the entire dynamic performance is as constraint condition,then the Non-dominated Sorting Genetic Algorithm-Ⅱ（ NSGA-Ⅱ） multi-objectives parameter optimization algorithm is proposed. The optimization results show that under the condition of meeting dynamic performance and good vehicle speed following effect,the average fuel economy increases by 5. 51%,the average emission increases by 14. 86%,the comfort performance meets with the riding requirements,and the maximum charging and discharging current reduces by half. Moreover,a series of global optimal solution of homogeneous distribution are obtained with the proposed algorithm,and the optimization results are satisfactory,which prove the proposed NSGA-Ⅱ multi-objectives parameter optimization algorithm is accurate and feasible.