摘要
文章针对设计的ISG型中度混合动力汽车(HEV),建立了基于动态规划算法优化控制策略的Matlab/Simulink逆向验证模型,通过仿真得到特定工况下燃油消耗最优值,用以评价之后建立的基于遗传算法优化的Advisor整车模型。比较仿真结果,可以得出基于遗传算法优化的Advisor模型具有较高的精确性,其燃油消耗量与理论最优油耗值误差在3.2%左右,总体油耗值在一个相对理想的范围。
According to the design of a moderate hybrid electric vehicle（HEV） with integrated starter and generator（ISG）, a reverse verification model usirig Matlab/Simulink was established, which was based on the dynamic programming algorithm to optimize the control strategy. The optimal fuel con- sumption value in specific driving cycle was given after running the simulation, which was used to e- valuate the vehicle model using Advisor based on genetic algorithm. The simulation results show that the model established by Advisor based on genetic algorithm has high accuracy~ compared to the theo- retical optimal fuel consumption value, the error is around 3.2% and overall fuel consumption value maintains in a relativelv ideal ran~
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2013年第9期1025-1028,共4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(2011AA11A202)
关键词
混合动力汽车
起动发电一体机
动态规划
遗传算法
hybrid electric vehicle（HEV）
integrated starter and generator（ISG）
dynamic program-ming
genetic algorithm
