文章针对纯电动中型客车传动系参数优化问题,以传动系中变速器的传动比为优化变量,以车辆动力性和经济性为优化目标,采用模型在环优化(non-optimization with model in loop,OML)方法,利用Simscape物理建模工具建立电动客车模型,结合带...文章针对纯电动中型客车传动系参数优化问题,以传动系中变速器的传动比为优化变量,以车辆动力性和经济性为优化目标,采用模型在环优化(non-optimization with model in loop,OML)方法,利用Simscape物理建模工具建立电动客车模型,结合带精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm NSGA-Ⅱ)对纯电动客车传动系参数进行优化,并基于最小二乘法组合赋权法进行Pareto解集选优确定出最优解。优化结果表明,利用OML方法在约束条件范围内合理地优化了变速器的传动比,加速时间和比能耗分别降低了6%和3.9%,达到了整车动力性和经济性协同优化的目的,为实车开发提供了理论参考。展开更多
A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An...A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude,pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square (RMS) of the vertical amplitude decreases by 37.2%,and 45.2% for the pitch angle,38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%,the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.展开更多
文摘文章针对纯电动中型客车传动系参数优化问题,以传动系中变速器的传动比为优化变量,以车辆动力性和经济性为优化目标,采用模型在环优化(non-optimization with model in loop,OML)方法,利用Simscape物理建模工具建立电动客车模型,结合带精英策略的非支配排序遗传算法(non-dominated sorting genetic algorithm NSGA-Ⅱ)对纯电动客车传动系参数进行优化,并基于最小二乘法组合赋权法进行Pareto解集选优确定出最优解。优化结果表明,利用OML方法在约束条件范围内合理地优化了变速器的传动比,加速时间和比能耗分别降低了6%和3.9%,达到了整车动力性和经济性协同优化的目的,为实车开发提供了理论参考。
文摘为了进一步提高ISG混合动力汽车的整车动力性与燃油经济性,在完成动力系统参数匹配之后,利用Advisor软件建立了仿真顶层模型,以验证参数匹配与部件选取的可行性;在此基础上,选取传动系主减速器速比和变速器各档速比为优化变量,动力性能相关要求为约束条件,采用粒子群优化(PSO)算法对传动系参数进行优化.仿真结果表明,优化后的最大爬坡度增加了4.3%,100 km燃油消耗降低了0.8 L,0~100 km/h加速时间减少了1.4 s.
基金Project(2010GK3091) supported by Industrial Support Project in Science and Technology of Hunan Province, ChinaProject(10B058) supported by Excellent Youth Foundation Subsidized Project of Hunan Provincial Education Department, China
文摘A neuron proportion integration (PI) control strategy for semi-active suspension system of tracked vehicle was proposed based on its unique structure and the multiple and complex environment of the driving traffic. An adaptive genetic algorithm is used to optimize the parameters of the neuron PI controller. The simulation result of the neuron PI control for semi-active suspension system of tracked vehicle indicates that the vertical amplitude,pitch angle and vertical acceleration of the vehicle are well controlled. The root mean square (RMS) of the vertical amplitude decreases by 37.2%,and 45.2% for the pitch angle,38.6% for the vertical acceleration. The research of neuron PI control experiment for the semi-active suspension system of the tracked vehicle model mining in benthal indicates that the RMS of the weight acceleration vibrating along the vertical direction decreases by 29.5%,the power spectral density resonance peak of the acceleration of the car body decreases by 23.8%.
