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基于NSGA-Ⅱ算法的磁流变悬置磁路多目标优化 被引量:19

Multi-objective Optimization for the Magnetic Circuit of Magneto-rheological Mount Based on NSGA-Ⅱ Algorithm
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摘要 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.
出处 《汽车工程》 EI CSCD 北大核心 2015年第5期554-559,共6页 Automotive Engineering
基金 中央高校基本科研项目(CDJZR13280074) 重庆大学机械传动国家重点实验室自主项目(0301002109165) 汽车噪声振动以及安全技术国家重点实验室开放基金资助
关键词 磁流变悬置 磁路 多目标优化 NSGA-II算法 magneto-rheological mount magnetic circuit multi-objective optimization NSGA-II algorithm
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参考文献11

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