基于粒子群算法的发动机悬置系统稳健优化设计  

Robust Optimal Design of an Engine Mounting System Based on Particle Swarm Optimization

作　　者：张武[1,2] 陈剑[1,3] 高煜[1] 

机构地区：[1]合肥工业大学噪声振动工程研究所,合肥230009 [2]安徽农业大学信息与计算机学院,合肥230036 [3]安徽省汽车NVH与可靠性重点实验室,合肥230009

出　　处：《农业机械学报》2010年第5期30-35,81,共7页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(50575063);国家"863"高技术研究发展计划资助项目(2006AA110101);安徽省科技攻关资助项目(060229E2)

摘　　要：应用稳健优化设计理论,考虑设计变量的变差对优化设计结果的影响,建立了稳健优化设计模型。以发动机悬置系统能量解耦为目标,悬置刚度参数为设计变量,考虑目标函数和约束函数均值μ和标准差σ的变化,构造了发动机悬置系统的稳健优化模型。采用粒子群优化算法对发动机悬置系统的悬置刚度参数进行了稳健优化设计,并用Monte Carlo方法进行了分析。设计应用表明,优化方法可以有效降低系统解耦度对悬置刚度参数的敏感性,系统解耦度分布更合理。比遗传算法的计算效率高。The result of design was affected by the variation of parameters,and the model of robust optimal design was established with the robust optimal design theory.Considering the variation in the mean value and variance of objective function and constraint function,the optimization model was built,which took decoupling of energy distribution as an objective,and stiffness parameters of mountings as a design variation.Particle swarm optimization（PSO） was adopted to optimize an engine mounting system to the stiffness of mountings,and the Monte Carlo method was used to analyze the optimization values.An example showed the method presented could decrease the sensitivity of decoupling with respect to the stiffness of mountings,and could make the vibration coupling distribution more reasonable.Comparing with the genetic algorithms,the optimization design computational efficiency of engine mounting system could be obtained quickly by PSO.

关 键 词：发动机悬置系统 稳健优化设计 能量解耦 粒子群 

分 类 号：TH122[机械工程—机械设计及理论] U463.33[机械工程—车辆工程]