Optimization design for powertrain mounting system of a hybrid electric vehicle via genetic algorithm

被引：0

作者：

Zhuang, Wei-Chao ^{[1
]}

Wang, Liang-Mo ^{[1
]}

Yin, Zhao-Ping ^{[2
]}

Ye, Jin ^{[2
]}

Wu, Hai-Xiao ^{[2
]}

机构：

[1] School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing

[2] Nanjing Iveco Automobile Co. Ltd., Nanjing

来源：

Zhendong yu Chongji/Journal of Vibration and Shock | 2015年 / 34卷 / 08期

关键词：

Energy decoupling; Genetic algorithm; Optimization; Powertrain mounting system;

D O I：

10.13465/j.cnki.jvs.2015.08.036

中图分类号：

学科分类号：

摘要：

A method to optimize a powertrain mounting system was developed to improve the vibration isolation performance of the mounting system for a parallel hybrid electric vehicle. The optimization was based on the genetic algorithm by taking 6-DOF energy decoupling of the powertrain mounting system and the reasonable allocation of the natural frequencies as the objectives, and taking the stiffnesses of 5 mounting points as the design variables. This method was applied to deal with the shaking of steering wheel for a parallel hybrid electric vehicle in its idling process. The results of dynamic simulation verified the effectiveness of the method. Furthermore, it was shown that compared to the sequential quadratic programming (SQP), the genetic algorithm overcomes its shortcoming of converging to local optimal solution, the decoupling features of the mounting system obtained from the optimization are better and reliable. ©, 2015, Chinese Vibration Engineering Society. All right reserved.

引用

页码：209 / 213

页数：4

共 9 条

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