基于遗传算法的混合动力汽车动力总成悬置系统的优化设计研究

为了提高并联式混合动力汽车动力总成五点悬置系统的隔振性能，建立了动力总成五点悬置的动力学模型，以动力总成六自由度能量解耦与固有频率的合理分配为优化目标，五个悬置点的各向刚度为设计变量，采用遗传算法对悬置系统进行优化。应用上述方法对某并联式柴电混合动力汽车悬置系统进行了优化，动力学仿真与实车试验结果表明，悬置优化后消除了整车怠速工况时方向盘抖动，验证了所提方法的合理性。同时，遗传算法克服了序列二次型规划算法（SQP）易收敛于局部最优解的缺点，得到的悬置系统解耦性能优良，优化结果稳定可靠。

Optimization Design on Powertrain Mounting System of Hybrid Electric Vehicle Via Genetic Algorithm

 A method to optimize the powertrain mounting system is developed to improve the vibration isolation performance of the mounting system for a parallel hybrid electric vehicle. The optimization is based on the genetic algorithm with taking the six-degree-freedom decoupling of the powertrain mounting system and the reasonable allocation of natural frequency as the objective function, and the stiffness of each mounting as the design variable. This method is applied to deal with the shaking of steering wheel for a parallel hybrid electric vehi-cle in idling process. And results of dynamics simulation verify the effectiveness of the method. Furthermore, compared to Sequential Quad-ratic Programming (SQP), genetic algorithm overcomes the fault, converging on local optimum. And the decoupling of mounting system obtained from the optimization is better and reliable.