基于遗传算法的汽车磁流变减振器多目标优化

Multi-objective Optimization of Vehicle MR Damper Based on Genetic Algorithm

为满足汽车半主动悬架系统的功能需求,宜设计具有大阻尼力调节范围、低能耗、响应迅速的磁流变减振器。本文中分别以磁流变减振器线圈耗能功率和响应时间为目标函数,以输出阻尼力和磁流变减振器阻尼通道处磁感应强度为约束条件,建立了磁流变减振器多目标优化模型,采用带精英策略的非支配排序遗传算法,获得了磁流变减振器多目标优化的最优Pareto解集。结果表明:多目标优化不仅能满足阻尼力可调范围的工程需求,且线圈功率损耗大大减小,响应时间明显缩短,为汽车磁流变减振器的结构优化提供了有效方法。。

To meet the functional requirements of vehicle semi-active suspension system, it is appropriate todesign a magneto-rheological （MR） damper with low energy consumption, quick response and a wide adjustablerange of damping force. In this paper, a multi-objective optimization model for MR damper is set up and NSGA-IIalgorithm is adopted to conduct a multi-objective optimization for MR damper, with its power consumption in coiland response time as objectives, and its output damping force and magnetic induction intensity at damping channelas constraints. An optimal Pareto solution set is then obtained and the results show that multi-objective optimizationnot only met the engineering requirements on the adjustable range of damping force, but also greatly reduce the powerconsumption in coil and significantly shorten response time, so providing an effective method for the structural optimizationof MR damper.