基于混合遗传算法的汽车动力总成悬置系统多目标优化  

Multi-objective optimization of powertrain mounting system based on hybrid genetic algorithm

作　　者：王金海[1] 周庆辉[1] 李波[2] 杨建伟[1] 

机构地区：[1]北京建筑大学机电与车辆工程学院,北京100044 [2]北京汽车研究总院,北京100021

出　　处：《机械设计》2014年第8期65-69,共5页Journal of Machine Design

基　　金：北京市教育委员会科技计划资助项目(KM201110016013);北京市属高校人才强教计划资助项目(201106125)

摘　　要：简述了动力总成悬置系统优化的能量解耦法和最小传递率优化方法。在此基础上,针对动力总成悬置系统的6自由度模型,使用一种新的并列分层多目标优化混合遗传算法,运用MATLAB对动力总成悬置的刚度进行了优化。结果表明,优化算法能够有效地完成优化工作并且可以使悬置系统的能量解耦率和传递率有明显的提高。Energy decoupling and minimizing transmissibility rate methods for optimization of powertrain mounting system were introduced in brief. Based on them, for 6-degree-of-freedom model of powertrain mounting system, a new hybrid Genetic Algorithm which mixed parallel selection method and hierarchical selection method was applied to optimize on MATLAB. As a result, the task of optimization can be done effectively using the optimization algorithm. Meanwhile, the energy decoupling rate and vibration transmitting rate of pitch mode and bounce mode are improved.

关 键 词：动力总成悬置系统 多目标优化 能量解耦 传递率 混合遗传算法 

分 类 号：U461.1[机械工程—车辆工程]