基于免疫算法的四驱插电式混合动力汽车控制策略多目标优化

摘要

To improve fuel economy and emission performance of a four-wheel drive PHEV,the rule-based energy management control strategy and vehicle simulation model were established firstly. Then,a multi-population immune algorithm was presented by introducing the concept of multi-popu-lation co-evolution.The algorithm was adopted to optimize the control strategies of four-wheel drive PHEV with multiple objectives.Finally,a hardware-in-the-loop simulation experiment was carried out on dSPACE real-time simulation system to test the control strategy before and after optimizations. Experimental results show that the optimized control strategy may achieve good control effectiveness, furthermore,the fuel consumption of engine is reduced by 12.71% while the HC,CO and NOx emis-sions are decreased by 15.74%,15.92% and 12.69% respectively.%为改善四驱插电式混合动力汽车的燃油经济性和排放性能,构建了基于规则的能量管理控制策略,并建立了整车仿真模型;将多种群协同进化的思想引入免疫算法,提出多种群免疫算法,并运用该算法对四驱插电式混合动力汽车的控制策略进行了多目标优化;在dSPACE实时仿真系统上对优化前后的控制策略进行了硬件在环仿真实验.结果表明:优化后的控制策略控制效果良好,且发动机的燃油消耗降低了12.71%,HC、CO以及NOx的排放分别下降了15.74%、15.92%和12.69%.