摘要
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。
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 energy 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 relationship. By introducing the diversity selection,vaccine injection and immune detection operators of immune algorithm into genetic algorithm,and improving the mode of vaccine selection and injecting,a novel IGA was constructed and adopted to optimize the overall control strategy with multiple objectives including fuel consumption and emission. The simulation results show that the proposed dual fuzzy control strategy realizes reasonable energy distribution 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.
出处
《电子测量与仪器学报》
CSCD
北大核心
2016年第2期209-217,共9页
Journal of Electronic Measurement and Instrumentation
基金
国家高技术研究发展计划(863计划)(SQ2010AA1122977001)
2012年国家新能源汽车技术创新工程(财建[2012]1095)
国家自然科学基金(51275002)项目资助
关键词
插电式混合动力汽车
模糊控制
免疫遗传算法
优化
plug-in hybrid electric vehicle
fuzzy control
immune genetic algorithm
optimization
作者简介
王永宽，2004年于合肥工业大学获得硕士学位，现为合肥工业大学博士研究生、安徽工业大学讲师。主要研究方向为电动汽车控制技术。E—mail：wyk5017@163．com钱立军，2004年于合肥工业大学获得博士学位，现为合肥工业大学教授、博士生导师。主要研究方向为电动汽车控制技术。E—mail：hfutqlj@163．com牛礼民，2008年于江苏大学获得博士学位，现为安徽工业大学副教授，主要研究方向为电动汽车控制技术。E—mail：niulimin@ahut．edu．cn
