基于NSGA-Ⅱ算法的磁流变悬置磁路多目标优化

Multi-objective Optimization for the Magnetic Circuit of Magneto-rheological Mount Based on NSGA-Ⅱ Algorithm

以磁流变悬置的磁路体积最小、输出阻尼力最大为优化目标,基于ANSYS参数化设计语言(APDL)建立了磁流变悬置磁路结构的多目标优化模型,采用带精英策略的快速非支配排序遗传算法(NSGA-II)进行优化,获得了磁路结构的Pareto最优解,并采用模糊集合理论对Pareto最优解进行选优。根据优化前后的磁路结构尺寸加工了两个磁流变悬置,并对悬置动态性能进行试验。结果表明:所提出的磁流变悬置磁路多目标优化方法是正确有效的,能够获得更加紧凑的磁流变悬置磁路结构,并提高悬置的输出阻尼力。

With minimizing the volume of magnetic circuit structure and maximizing its output damping force as optimization objectives, a multi-objective optimization model for the magnetic circuit structure of magnetorheological （MR） mount is established with ANSYS parametric design language （APDL）. An optimization is conducted with the fast elitist non-dominated sorting genetic algorithm （NSGA-II） and a pareto optimal set is obtained, from which the best compromise solution is extracted based on fuzzy set theory. Two MR mounts with magnetic cir- cuit structures before and after optimization are manufactured respectively and tested on their dynamic performance. The results show that the multi-objective optimization scheme proposed is correct and effective in achieving a more compact magnetic circuit structure with an increased output damping force.