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基于Taguchi方法的动力总成悬置系统稳健优化 被引量:19

Robust Optimization of Powertrain Mounting System Based on Taguchi Method
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摘要 为提高动力总成悬置系统的隔振性能及其优化设计的稳健性,首先建立悬置系统6自由度模型,并以各自由度方向的解耦率最大为目标,以各悬置点三向刚度为设计变量,选用遗传算法对悬置刚度参数进行初步优化;接着选择解耦率高且刚度分布合理的个体作为对象,以信噪比作为评价指标,应用Taguchi方法进行一次或者多次稳健优化,获得较为理想的优化解;最后应用蒙特卡罗方法进行稳健分析。结果表明,该方法在保证刚度合理分布的基础上,能有效提高各自由度方向上的解耦率,增强悬置系统的稳健性。 In order to improve the vibration isolation performance and the optimization robustness of powertrain mounting system, a 6 DOF dynamics model for the mounting system is built first and a preliminary optimization on its stiffness parameters is conducted by using genetic algorithm with maximizing decoupling rate of 6 DOFs as objective and the stiffnesses in three directions of each mount as design variables. Then among the outcomes of preliminary optimization, the one with high decoupling rate and reasonable stiffness distribution is selected as object with signal to noise ratio as evaluation indicator, one or more robust optimizations are carried out by applying Taguchi method and a more desired optimized solution is obtained. Finally, a robustness analysis is performed with Monte Carlo technique. The results show that the scheme can effectively improve the decoupling rate of 6 DOFs and enhance the robustness of mounting system, while ensuring the reasonable distribution of stiffness.
出处 《汽车工程》 EI CSCD 北大核心 2014年第4期475-480,514,共7页 Automotive Engineering
基金 国家自然科学基金(50975071)资助
关键词 动力总成 悬置系统 稳健性 遗传算法 Taguchi方法 蒙特卡罗方法 powertrain mounting system robustness genetic algorithms Taguchi method Monte Carlo method
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