利用ADAMS/Car模块建立了某车麦弗逊式前悬架系统模型,为优化该悬架结构,运用ADAMS/Insight对悬架参数进行了灵敏度分析,根据分析结果和相关参数的设计要求,运用遗传算法对该悬架系统进行优化。在ADAMS/Car中分别对优化前后的悬架进行双轮同向激振仿真试验,对比前轮定位参数的变化量和变化范围。结果表明,前轮主要定位参数的变化量减小,改善了悬架的运动学特性,达到了优化目的,为汽车悬架的设计提供了依据。 In order to optimize the suspension structure, the ADAMS / Car module is used to analyze the sensitivity of the suspension parameters. According to the analysis results and the design requirements of the related parameters, The genetic algorithm optimizes the suspension system. In ADAMS / Car, the wheel suspension with two wheels before and after the same direction excitation test was simulated respectively to compare the change amount and range of the front wheel alignment parameters. The results show that the variation of the main positioning parameters of the front wheel is reduced, the kinematic characteristics of the suspension are improved, and the optimization purpose is achieved, which provides the basis for the design of the automobile suspension.