基于遗传算法的12自由度动力总成悬置系统多目标优化

Multi-objective Optimization of Twelve Degrees of Freedom Powertrain Mounting System Based on Genetic Algorithm

以某乘用车为研究对象,建立了包括动力总成和车身两个刚体的12自由度动力总成悬置系统模型。以能量解耦及怠速隔振量为目标函数,综合考虑悬置主簧结构及刚体模态频率分布的约束要求,采用遗传算法对动力总成悬置系统解耦率及怠速隔振量进行多目标优化。仿真结果与试验结果表明,该方法能有效优化动力总成悬置系统。

Taking a car as study object, a dynamic model of twelve degrees of freedom powertrain mounting system was established which included powertrain and body. Taking energy decoupling rate and vibration isolation in idle as objective functions, considering the main spring structure and frequency distribution of rigid body as constraint conditions, multi-objective optimization aiming at energy decoupling rate and vi- bration isolation of the powertrain mounting system was carried based on genetic algorithm. The results of simulation and real vehicle test verify the effectiveness of the method proposed.