考虑车内振动的动力总成悬置系统多目标优化

摘要/Abstract

摘要：

以实际工况下的测试数据为基础，建立了简化的车内振动传递路径分析模型。在此基础上，以发动机悬置刚度为设计变量，综合考虑悬置系统能量解耦和车内振动，建立了基于灰色粒子群优化算法的多目标优化模型。并以某型卡车为例，进行了多目标优化求解。实验和优化结果表明,在得到较好能量解耦的同时,降低了车内振动,实现了能量解耦和车内低振动的优化匹配。

关键词: 动力总成悬置系统, 传递路径分析, 灰色粒群算法, 蒙特卡罗法

Abstract:

Simplified vehicle vibration TPA model was established based on the actual transfer path test datum. On the basis of that, multi-objective optimization model of powertrain mount system was established based on GPSO algorithm with considering energy decoupling and vehicle vibration, mounting stiffness parameters were taken as design variables. Taking a truck for example, a multi-objective optimization solution was conducted. The test and optimization results show that the optimization method can get better energy decoupling and lower vehicle vibration, while achieving the optimal matching of energy decoupling and cars and low vibration.

Key words: powertrain mounting system, transfer path analysis(TPA), grey particle swarm optimization(GPSO), Monte Carlo method

中图分类号:

U463.33

陈剑, 史韦意, 蒋丰鑫, 曾维俊, 沈忠亮, 汪一峰. 考虑车内振动的动力总成悬置系统多目标优化[J]. 中国机械工程, 2015, 26(8): 1129-1135.

Chen Jian, Shi Weiyi, Jiang Fengxin, Zeng Weijun, Shen Zhongliang, Wang Yifeng. Multi-objective Optimization of Powertrain Mount System Concurrently Considering Energy Decoupling and Vehicle Vibration[J]. China Mechanical Engineering, 2015, 26(8): 1129-1135.

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http://www.cmemo.org.cn/CN/Y2015/V26/I8/1129

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