基于Pareto集和Bingham模型的磁流变减振器多目标优化与试验验证

Multi-objective optimization and experimental verification of magnetorheological damper based on Pareto set and Bingham model

磁流变减振器和半主动悬架可以同时兼顾车辆操纵稳定性和行驶安全性,是目前汽车电子技术的研究热点。磁流变减振器的设计大多只考虑某一优化目标,基于Pareto集多目标方法和带精英策略的非支配排序遗传算法(the elitist Nondominated Sorting Genetic Algorithm,NSGA-Ⅱ),以阻尼力和动力可调系数为优化目标,设定7个优化变量,构建了车用磁流变减振器多目标优化模型与实现算法。分析了7个优化变量对阻尼力和动力可调系数的设计敏感性,并通过有限元分析和试验验证优化解的可靠性。研究发现:阻尼通道间隙对优化目标影响最大,最大阻尼力和最大动力可调系数呈负相关关系。该多目标优化计算的最优解满足实际工程需求,证明了提出的优化方法快速有效,为磁流变减振器的设计提供了可靠的工具。

Magnetorheological damper and semi-active suspension can simultaneously consider the handling stability and drive safety of vehicle,and it is a research hotspot of automotive electronics technology.Most of the design of magnetorheological damper only considers a certain optimization goal.Based on Pareto set multi-objective method and the elitist nondominated sorting genetic algorithm,it set the optimization variables with damping force and dynamic adjustable coefficient,and set seven optimization variables to establish a multi-objective optimization model and implementation algorithm for magnetorheological damper for vehicles.The sensitivity of seven design variables to damping force and dynamic adjustable coefficient was analyzed,and the reliability of the optimized solution was verified by finite element analysis and test.It is found that the gap of the damping channel have the greatest influence on the optimization goal,and the maximum damping force and the maximum dynamic adjustment coefficient are negatively correlated.The optimal solution of the multi-objective optimization calculation satisfies the actual engineering requirements,which proves that the proposed optimization method is fast and effective,and provides a reliable tool for the design of the magnetorheological damper.