四川大学学报：工程科学版2012，Vol.44Issue(3)：141-146,6.
基于进化算法的带约束混合动力系统多目标优化
Constrained Parallel Hybrid System Multi-objective Optimization Based on Evolutionary Algorithm
摘要
Abstract
In order to obtain a method to avoid transforming multi-objective functions into a single objective evaluation function for hybrid system multi-objective optimization problem,the parallel hybrid electric vehicle model was analyzed,the multi-objective optimization mathematical model of constrained hybrid system was established,and the optimization objectives,parameters and constraints were given.A multi-objective evolutionary algorithm for constrained parallel hybrid system optimization based on NSGA-Ⅱ（cPHS-NSGA） was proposed,which adopted the Pareto dominated principle to determine solutions without specifying weight coefficient for each objective.The simulation optimization results showed that compared with the old system,the fuel consumption per 100 km dropped by an average of 0.25% and the emissions fell by an average of 2.75%.Battery charging efficiency distribution changed from [0.8,0.9] to [0.85,0.9] and the range of discharge efficiency changed from [0.82,1.0] to [0.95,1.0].The cPHS-NSGA was capable to improve the performance of parallel hybrid system.关键词
多目标优化/混合动力系统/混合动力汽车/进化算法Key words
multi-objective optimization/hybrid system/hybrid electric vehicle/evolutionary algorithm分类
交通运输引用本文复制引用
杨观赐,李少波,璩晶磊,钟勇,于新宝..基于进化算法的带约束混合动力系统多目标优化[J].四川大学学报：工程科学版,2012,44(3):141-146,6.基金项目
教育部新世纪优秀人才支持计划资助项目 （）
国家“863”计划资助项目 （）
“十二五”国家科技支撑计划资助项目 （）
贵州省科学技术基金资助项目 （）
