Optimization of Automotive Powertrain Mounting System Based on Adaptive Genetic Algorithm

机译：基于自适应遗传算法的汽车动力总成悬置系统优化

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There are many local optimization solutions to optimize the automotive powertrain mounting system with conventional optimum algorithms which are likely to get trapped in local minima. To overcome this fault, taking the kinetic energy decoupling level as the objective function, stiffness of each mounting served as the design variable, adaptive genetic algorithm which was programmed in the MATLAB software was applied. The corresponding simulation model was built in ADAMS software to verify the result of the adaptive genetic algorithm. The optimum results show that the decoupling effect has been improved.

机译：有许多本地优化解决方案可以使用传统的最佳算法来优化汽车动力总成安装系统，而这些算法可能会陷入局部极小值中。为了克服该故障，以动能解耦水平为目标函数，以每个安装座的刚度为设计变量，应用了在MATLAB软件中编程的自适应遗传算法。在ADAMS软件中建立了相应的仿真模型，以验证自适应遗传算法的结果。最佳结果表明，去耦效果得到了改善。

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《International Symposium on Intelligent Information Technology Application;IITA 2009》|2009年|347-350|共4页
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Jiang-hua Fu; Wen-ku Shi; Teng Teng; Zu-bin Liu;
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ADAMS; MATLAB; decoupling; genetic algorithm; mounting; optimization; powertrain;

机译：ADAMS; MATLAB;解耦;遗传算法;安装;优化;动力总成;

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Optimization of Automotive Powertrain Mounting System Based on Adaptive Genetic Algorithm

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