摘要
为提高某重型汽车的动力性和经济性,对其传动系参数进行了多目标优化。利用CRUISE软件建立了该车型的仿真模型。为提高优化速度,建立了CRUISE仿真模型的响应面模型作为优化时的代理模型。利用Matlab遗传算法工具箱对代理模型进行了优化。将优化所得PARETO最优解集回代到CRUISE仿真模型,根据CRUISE计算的目标函数值对所得PARETO最优解集进行修正。修正后可作为CRUISE模型的PARETO最优解。结果表明:采用的优化方法不仅降低了优化时间,而且可为设计人员提供更大的选择空间。
Multi-objective optimization of a heavy-duty truck transmission′s parameters is done for improving the driving and economy performance.A simulation model of the truck is set up using CRUISE software.The least square response surface model of the simulation model is used as a surrogate for saving time when optimization is being done using genetic algorithm toolbox in Matlab.The values of objective functions at each PARETO solution are calculated by CRUISE,and the PARETO solutions are modified based on the objective function values from CRUISE.The modified PARETO solutions can be used as PARETO solutions of CRUISE model.The results show that this method can not only save time but also provide more choices for designers.
出处
《机械科学与技术》
CSCD
北大核心
2011年第9期1569-1572,1578,共5页
Mechanical Science and Technology for Aerospace Engineering
关键词
最小二乘响应面法
多目标优化
重型汽车传动系匹配
代理模型
least square response surface method
multi-objective optimization
heavy-duty truck transmission matching
surrogate model