Fast Analysis and Optimization of a Magnetic Gear Based on Subdomain Modeling

This study presents a two-dimensional analytical method for fast optimization, taking into consideration the influence of the eddy current in a magnet and iron loss within a coaxial magnetic gear. Subdomain modeling was utilized to obtain vector potentials in the air-gap, magnet, and modulation regions by solving Maxwell’s equations. After that, the magnet, rotor, and modulation losses were predicted and then compared using a finite element method simulation within three topologies with gear ratios ranging from five to six. The authors improved the machine performance, specifically the torque density, by employing a multi-objective function with particle swarm optimization. The flux density obtained using subdomain modeling in just 0.5 s benefits the optimization process, resulting in a torque-density optimal model after around 3 h. A 3/19/16 prototype targeting a low-speed, high-torque, permanent generator application was fabricated to verify the analytical and simulation results.

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Publication Details

Journal
Mathematics
Published
2024-09-20
DOI
https://doi.org/10.3390/math12182922
Citations
9
Primary Topic
Electric Motor Design and Analysis
Type
article
Field-Weighted Citation Impact
1.88
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Fast Analysis and Optimization of a Magnetic Gear Based on Subdomain Modeling

Kyung-Hun Shin, Jang-Young Choi, Duy-Tinh Hoang, Woo-Sung Jung et al.
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article

Fast Analysis and Optimization of a Magnetic Gear Based on Subdomain Modeling

Kyung-Hun Shin, Jang-Young Choi, Duy-Tinh Hoang, Woo-Sung Jung, Manh-Dung Nguyen, Yong‐Joo Kim
article en
9 citations

Abstract

This study presents a two-dimensional analytical method for fast optimization, taking into consideration the influence of the eddy current in a magnet and iron loss within a coaxial magnetic gear. Subdomain modeling was utilized to obtain vector potentials in the air-gap, magnet, and modulation regions by solving Maxwell’s equations. After that, the magnet, rotor, and modulation losses were predicted and then compared using a finite element method simulation within three topologies with gear ratios ranging from five to six. The authors improved the machine performance, specifically the torque density, by employing a multi-objective function with particle swarm optimization. The flux density obtained using subdomain modeling in just 0.5 s benefits the optimization process, resulting in a torque-density optimal model after around 3 h. A 3/19/16 prototype targeting a low-speed, high-torque, permanent generator application was fabricated to verify the analytical and simulation results.

MathematicsVol. 12(18)
Changwon National University (KR), Chungnam National University (KR)
Affordable and clean energy
Openalex Percentile: Top 14%
Electric Motor Design and Analysis
1.88
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