Abstract: Considering the influence of the uncertainty of design variables on the optimization design, the robust optimization design theory was used to build a robust model for the powertrain mounting system of automobiles. In this model, decoupling of energy distribution was taken as the target, the stiffness parameters of the mounting was taken as a design variable, and the mean and standard deviation of the target results were considered. Aiming at the problem that the particle swarm algorithm was easy to fall into a local optimal solution, a hybrid particle swarm algorithm was adopted to optimize the stiffness of the mounting of the powertrain mounting system, and the Monte Carlo method was used to analyze the optimized results to examine the influence of the variety of design values on the objective function. The results show that the method can improve the robustness of the mounting system effectively.

Key words: vibration and wave , powertrain mounting system , robust optimization , hybrid particle swarm

摘要： 应用鲁棒优化设计理论，考虑设计变量的不确定性对优化设计结果的影响，建立鲁棒优化模型。以动力总成悬置系统能量解耦为目标，悬置刚度参数为设计变量，考虑设计目标的均值和标准差，建立动力总成悬置系统的鲁棒优化模型。针对粒子群算法求解容易陷入局部最优解的问题，采用混合粒子群算法对动力总成悬置系统的悬置刚度参数进行鲁棒优化，并用Monte Carlo方法进行分析，以考察设计值的变化对目标函数的影响。结果表明，优化方法可以有效提高悬置系统的鲁棒性。

关键词: 振动与波, 动力总成悬置系统, 鲁棒优化, 混合粒子群