摘要
以CVT插电式混合动力汽车为研究对象,对动力传动系统进行匹配。在matlab/simulink平台上,建立了以整车消耗成本为目标,以动力性设计指标为约束,以发动机功率、电机功率、电池容量、减速器速比为变量的优化模型,利用量子遗传算法进行求解,得到了整车消耗成本最小的部件参数,并建立系统仿真模型进行了仿真。结果表明,在15个NEDC工况下,经过该方法优化后整车消耗成本降低约6.33%。
Taking continuously variable transmission(CVT) plug-in hybrid electric vehicle as the study subject, the power train is matched. On the Matlab/Simulink platform, the optimization mode aiming at minimizing the vehicle consumption costs was built. Under the constraints of dynamic design specifications, the quantum genetic algorithm has been used to find the global optimal parameters including engine power, motor power, battery capacity and reducer speed ratio. The result shows that the vehicle consumption cost after optimization is 6.33% less than before optimization in fifteen driving cycles of the NEDC.
出处
《内燃机》
2014年第6期29-32,36,共5页
Internal Combustion Engines
关键词
混合动力
CVT
插电式
量子遗传算法
整车消耗成本
hybrid electric
CVT
plug-in
quantum genetic algorithm
vehicle consumption costs
