An Efficient Robust Design Optimization Approach of Electromagnetic Relay Based on Surrogate Model and Evolutionary Algorithm

Hao Chen, X. Ye, Yigang Lin, G. Zhai
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引用次数: 0

Abstract

The reliability and robustness of electromagnetic relay's performance characterize directly related to the performance, reliability and robustness of the aviation, aerospace, intelligent equipment industry, and its design and optimization have initiated boundless concern. The efficiency of the calculation of performance characteristics and the accuracy of the optimization process are two critical aspects affecting the design optimization of electromagnetic relay reliability and robustness. In response to the above issues, this study proposed an efficient computational burden reduction strategy for the multi-objective design and optimization aimed at the electromagnetic relay with substantial non-linearity and insufficient convergence characteristics. The dual response surface approach extracted the surrogate model of the mean value and variance for the critical static attractive force point. On the basis of the surrogate model, a particle swarm evolutionary algorithm for multi-objective design and optimization of electromagnetic relay has been modified. Then, the modified particle swarm evolutionary algorithm was used to optimize the dual response surface model, verifying the algorithm's feasibility. At last, the effectiveness of the proposed approach in this study was verified by a case study of the differential polarized magnetically maintained electromagnetic relay double permanent magnets.
基于代理模型和进化算法的电磁继电器稳健设计优化方法
电磁继电器性能的可靠性和鲁棒性直接关系到航空、航天、智能装备行业的性能、可靠性和鲁棒性,其设计与优化引起了人们的广泛关注。性能特性计算的效率和优化过程的准确性是影响电磁继电器设计优化的可靠性和鲁棒性的两个关键方面。针对上述问题,本研究针对电磁继电器非线性较大、收敛性不足的特点,提出了一种高效的多目标设计优化计算量减少策略。双响应面法提取了临界静力点均值和方差的替代模型。在此模型的基础上,改进了电磁继电器多目标设计与优化的粒子群进化算法。然后,利用改进的粒子群进化算法对双响应面模型进行优化,验证了算法的可行性。最后,以差动极化磁保持电磁继电器双永磁体为例,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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