基于遗传算法和ADAMS的麦弗逊悬架优化研究

为了改善汽车麦弗逊前独立悬架的运动学特性,从而解决轿车前轮胎磨损较严重的问题,将遗传算法与机械系统动力学自动分析软件ADAMS相结合,根据悬架空间结构建立了麦弗逊悬架理论模型,利用ADAMS/View建立了该轿车的麦弗逊前悬架虚拟样机模型,利用ADAMS自带OPTDES GRG算法和用户自定义的遗传算法,选择对轮距变化影响较大的悬架结构参数作为设计变量,分别对该轿车的麦弗逊前悬架虚拟样机模型进行优化设计.经过2种算法的优化,悬架的运动学特性得到了不同程度的改善；而且通过2种算法优化结果的比较,得出了遗传算法和ADAMS软件相结合的优化设计方法在汽车悬架参数优化问题中的优越性、可行性.

The research on optimization of Macpherson suspension based on genetic algorithm and ADAMS

To improve the kinematic characteristics of front Macpherson suspension and solve the front wheels wear problem,the independent suspension system of a car was studied.The genetic algorithm and ADAMS(automatic dynamic analysis of mechanical systems)software were combined together.According to spatial structure of Macpherson suspension,its theoretical model was established.A virtual prototype model of front Macpherson suspension was built by using the ADAMS/View module.The virtual prototype model of suspension was optimized with two methods,which were the OPTDES-GRG algorithm of ADAMS software and the genetic algorithm combined with ADAMS software.For optimization,the Macpherson suspension structure parameters which had great influence on the wheel track change were chosen as the design variables.After the two algorithm’s optimization,the kinematics characteristic of suspension get different degrees of improvement.By comparing the optimization results of the two algorithms,the genetic algorithm combined with ADAMS software has the superiority and feasibility.