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Multi-objective genetic algorithm optimization of linear proportional solenoid actuator
Journal of the Brazilian Society of Mechanical Sciences and Engineering ( IF 1.8 ) Pub Date : 2021-01-15 , DOI: 10.1007/s40430-020-02768-7
Shi Jie Wang , Zhi Dan Weng , Bo Jin , Hong Xu Cai

Linear proportional solenoid (LPS) is widely applied in different linear motion control systems as the electromagnetic actuator since its high reliability and low cost. LPS is difficult to optimize by changing a single variable due to amounts of structural design parameters, and each design parameter has a nonlinear relationship with the static electromagnetic force. This paper aims to improve LPS’s push force and response performance through magnetostatic finite element analysis (FEA) by ANSYS MAXWELL. This study compares FEA 2D model, 3D model and measurement results underrated coil current to verify the accuracy of FEA 2D model. In order to reveal the nonlinear relationship between shape design parameters and electromagnet design objectives, this study compares the influence degree of each variable on each design objective by conventional type LPS 2D FEA model. And for the purpose of improving LPS’s push force and response performance, a multi-objective optimization method has been proposed in this study based on genetic algorithm (GA) and magnetostatic FEA 2D model for optimizing the shape design parameters. All the study results were validated in both static conditions and dynamic conditions. The comparison between manufactured optimal type and conventional type results shows that the static push force in working stroke is improved 30.1%, displacement step response rise time is reduced 5.2% and 43.4%, and force step response rise time is reduced 20.5% and 44.6% with different return spring stiffness. Above all, LPS static and dynamic performance has been improved directly and the validation of proposed optimization method is verified in this paper.



中文翻译:

线性比例电磁执行器的多目标遗传算法优化

线性比例螺线管(LPS)具有高可靠性和低成本,因此广泛应用于各种线性运动控制系统中作为电磁执行器。由于结构设计参数的数量,很难通过更改单个变量来优化LPS,并且每个设计参数与静态电磁力都具有非线性关系。本文旨在通过ANSYS MAXWELL的静磁有限元分析(FEA)来提高LPS的推力和响应性能。本研究比较了FEA 2D模型,3D模型和低估线圈电流的测量结果,以验证FEA 2D模型的准确性。为了揭示形状设计参数与电磁体设计目标之间的非线性关系,本研究通过常规LPS 2D FEA模型比较了每个变量对每个设计目标的影响程度。为了提高LPS的推力和响应性能,提出了一种基于遗传算法(GA)和静磁FEA 2D模型的多目标优化方法,以优化形状设计参数。所有研究结果均在静态和动态条件下得到验证。制造的最佳类型和常规类型结果的比较表明,工作行程中的静态推力提高了30.1%,位移阶跃响应上升时间减少了5.2%和43.4%,力阶跃响应上升时间减少了20.5%和44.6%具有不同的复位弹簧刚度。首先,

更新日期:2021-01-15
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