基于Isight的增程式电动汽车控制参数多目标优化  

Multi-objective optimization of control parameters of range-extended electric vehicle based on Isight

作　　者：尹安东[1] 董欣阳 张冰战[1] 江昊[1] 

机构地区：[1]合肥工业大学机械与汽车工程学院,安徽合肥230009

出　　处：《合肥工业大学学报（自然科学版）》2015年第3期289-294,共6页Journal of Hefei University of Technology：Natural Science

基　　金：国家"863"节能与新能源汽车重大资助项目(2012AA111401);安徽省自然科学基金资助项目(1208085ME78)

摘　　要：文章以某款增程式电动汽车(range-extended electric vehicle,REEV)为研究对象,设计了整车控制策略,借助整车性能仿真软件CRUISE和多学科设计优化软件Isight搭建了整车性能仿真和优化模型,并采用改进的非支配排序遗传算法(non-dominated sorting genetic algorithm,NSGA-Ⅱ)对增程器控制参数进行多目标优化。优化结果表明,在满足整车能量需求的前提下,优化后的增程器总发电量减少了7.34%,汽车百公里燃油消耗量降低了8.28%。A range-extended electric vehicle（REEV）was studied,and a control strategy was designed.The simulation model was established by using the vehicle simulation software CRUISE and the multiobjective optimization software Isight,and the control parameters were optimized with an improved non-dominated sorting genetic algorithm（NSGA-Ⅱ）.The result showed that the power generated by the range-extender could meet the need of vehicle.And the range-extender could reduce the total electric power by 7.34% as well as the fuel consumption per 100 kilometers by 8.28%.

关 键 词：增程式电动汽车 Isight软件 控制参数 多目标优化 非支配排序遗传算法 

分 类 号：U469.72[机械工程—车辆工程]