插电式混合动力汽车双模糊控制策略及其优化

提出一种免疫遗传算法优化的插电式混合动力汽车双模糊控制策略。采用模糊控制方法,分别以发动机工作区间最优和制动能量回收最大为原则,建立了能量管理驱动控制策略和制动控制策略,并根据两者的耦合关系将它们组合成整体控制策略。通过将免疫算法的多样性选择算子、疫苗注射算子、免疫检测算子引入遗传算法,并对疫苗的选择和注射方式予以改进,构成新的免疫遗传算法,应用该算法对控制策略进行了兼顾油耗和排放的多目标优化。仿真结果表明:所提出的双模糊控制策略能实现汽车能量的合理分配,优化后的油耗和三种排放物的排放分别降低了14.01%、12.27%、11.81%和20.34%,且优化结果明显好于遗传算法的结果。

Dual fuzzy control strategy and its optimization for plug in hybrid electric vehicle

A dual fuzzy control strategy optimized by immune genetic algorithm ( IGA) was proposed for a plug-in hybrid electric vehicle (PHEV).With the principle of optimal engine operating region and maximum braking ener-gy recovery, the driving and braking control strategies of energy management were established using fuzzy control method.These two control strategies were integrated into the overall control strategy based on their coupling rela-tionship.By introducing the diversity selection, vaccine injection and immune detection operators of immune algo-rithm into genetic algorithm, and improving the mode of vaccine selection and injecting, a novel IGA was construc-ted and adopted to optimize the overall control strategy with multiple objectives including fuel consumption and e-mission.The simulation results show that the proposed dual fuzzy control strategy realizes reasonable energy distri-bution in PHEV.The optimized fuel consumption and three kinds of emissions are reduced by 14.01%, 12.27%, 11.81% and 20.34% respectively.And IGA achieves better optimal result than that genetic algorithm does.