基于遗传算法的ISG混合动力汽车参数优化  

Parameter Optimization of ISG Hybrid Electric Vehicle Based on Genetic Algorithm

作　　者：尹安东[1] 谌文文[1] 赵韩[1] 路瑞刚[2] 冯瑞[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,合肥230009 [2]中国汽车工程学会,北京100055

出　　处：《汽车工程》2011年第10期834-837,共4页Automotive Engineering

基　　金：国家"863"节能与新能源汽车重大项目(2008AA11A139)资助

摘　　要：利用仿真软件CRUISE建立某一轻度混合动力汽车的仿真模型。以加速时间和100km油耗为优化目标,采用带精英策略的快速非支配排序遗传算法对其动力传动系统的速比参数进行优化。结果表明,优化后在满足汽车动力性设计指标的前提下,汽车在NEDC工况下的油耗降低了7.05%。A simulation model for the power-train of a ISG HEV is established using CRUISE software.An optimization on the gear ratio parameters of power-train is performed by adopting fast elitist non-dominated sorting genetic algorithm（NSGA-Ⅱ） with acceleration time and fuel consumption as objectives.The results show that after optimization the fuel consumption of vehicle with NEDC cycle reduces by 7.05% on the premise of meeting the design specifications of vehicle power performance.

关 键 词：混合动力汽车 ISG 动力传动系统 非支配排序遗传算法 优化 

分 类 号：U469.7[机械工程—车辆工程]