摘要
为带双离合器和单轴转矩耦合的某并联混合动力汽车开发了模糊控制策略,采用遗传算法对转矩分配模糊控制器进行了优化。在Matlab/Simulink和ADVISOR环境下基于试验数据建立了仿真模型,并进行了NEDC循环下只考虑经济性的控制策略优化和综合考虑经济性和排放性能的多目标控制策略优化。结果表明,应用遗传算法对模糊控制策略进行多目标优化后,油耗降低了3.65%,同时整车排放也有明显降低。
A fuzzy control strategy is developed for a parallel hybrid electric vehicle with dual-clutch and single-axis torque coupling.Then the genetic algorithm（GA） is adopted to optimize the fuzzy control strategy for torque distribution.Specifically,a simulation model is built with Matlab/Simulink and ADVISOR based on test data,and the optimizations on control strategy with both single objective of fuel economy and multi-objectives of fuel economy and emission performance are conducted under NEDC driving cycle.The results show that after multi-objective optimization on fuzzy control strategy using GA,fuel consumption reduces by 3.65% with exhaust emission also decreasing apparently.
出处
《汽车工程》
EI
CSCD
北大核心
2011年第2期106-111,共6页
Automotive Engineering
基金
囯家“863”计划项目(2006AA11A112)资助
关键词
并联混合动力汽车
遗传算法
模糊控制
优化
parallel hybrid electric vehicle
genetic algorithm
fuzzy control
optimization
