Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm

doi:10.1088/1674-1056/ae0b38

中国物理B ›› 2026, Vol. 35 ›› Issue (4): 40701-040701.doi: 10.1088/1674-1056/ae0b38

Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm

Yu-Xiao Wang(王雨潇)^1,2, Shi-Yu Guan(管世钰)^1,2, Yi Zhang(张燚)^1,2, Qi-Yuan Jiang(江奇渊)^1,2, Bing-Feng Sun(孙兵锋)^1,2, and Zhong-Qi Tan(谭中奇)^1,2,†

1 College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China;
2 Nanhu Laser Laboratory, National University of Defense Technology, Changsha 410073, China

收稿日期:2025-07-04 修回日期:2025-09-05 接受日期:2025-09-25 发布日期:2026-03-26
通讯作者: Zhong-Qi Tan E-mail:zhqitan@sina.com
基金资助:
This work was supported by the Natural Science Foundation of China (Grant No. 62375285) and the Research Project of the National University of Defense Technology (Grant No. 24-ZZCX-XXXX-01-04).

Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm

Yu-Xiao Wang(王雨潇)^1,2, Shi-Yu Guan(管世钰)^1,2, Yi Zhang(张燚)^1,2, Qi-Yuan Jiang(江奇渊)^1,2, Bing-Feng Sun(孙兵锋)^1,2, and Zhong-Qi Tan(谭中奇)^1,2,†

1 College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China;
2 Nanhu Laser Laboratory, National University of Defense Technology, Changsha 410073, China

Received:2025-07-04 Revised:2025-09-05 Accepted:2025-09-25 Published:2026-03-26
Contact: Zhong-Qi Tan E-mail:zhqitan@sina.com
Supported by:
This work was supported by the Natural Science Foundation of China (Grant No. 62375285) and the Research Project of the National University of Defense Technology (Grant No. 24-ZZCX-XXXX-01-04).

摘要/Abstract

摘要： This study introduces a structural optimization method for magnetic flux concentrators (MFCs) utilizing the particle swarm optimization (PSO) algorithm, addressing inefficiencies and challenges in achieving optimal structures with traditional methods. By integrating the PSO algorithm with COMSOL Multiphysics simulation software, a co-simulation framework is developed to optimize the parameters of a conical MFC. Compared with traditional methods, this approach enhances optimization results by twofold, achieving a magnetic field amplification factor of up to 200 within the defined parameter range. Additionally, an evaluation criterion for concentrator optimization is proposed, offering novel insights for designing concentrators across various scenarios.

关键词: magnetic flux concentrator, magnetic sensing enhancement, particle swarm optimization

Abstract: This study introduces a structural optimization method for magnetic flux concentrators (MFCs) utilizing the particle swarm optimization (PSO) algorithm, addressing inefficiencies and challenges in achieving optimal structures with traditional methods. By integrating the PSO algorithm with COMSOL Multiphysics simulation software, a co-simulation framework is developed to optimize the parameters of a conical MFC. Compared with traditional methods, this approach enhances optimization results by twofold, achieving a magnetic field amplification factor of up to 200 within the defined parameter range. Additionally, an evaluation criterion for concentrator optimization is proposed, offering novel insights for designing concentrators across various scenarios.

Key words: magnetic flux concentrator, magnetic sensing enhancement, particle swarm optimization

中图分类号: (Magnetometers for magnetic field measurements)

07.55.Ge

02.60.Pn (Numerical optimization) 75.50.-y (Studies of specific magnetic materials) 87.55.de (Optimization)

Yu-Xiao Wang(王雨潇), Shi-Yu Guan(管世钰), Yi Zhang(张燚), Qi-Yuan Jiang(江奇渊), Bing-Feng Sun(孙兵锋), and Zhong-Qi Tan(谭中奇). Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm[J]. 中国物理B, 2026, 35(4): 40701-040701.

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Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm

Structural optimization of magnetic flux concentrator based on particle swarm optimization algorithm

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