Comparative Analysis and Design Optimization of Ferrite-Based Surface PM Vernier Machines

Gwan-Hui Jang, Abdur Rehman and Gilsu Choi ()
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Gwan-Hui Jang: Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea
Abdur Rehman: Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea
Gilsu Choi: Department of Electrical and Computer Engineering, Inha University, Incheon 22212, Republic of Korea

Energies, 2024, vol. 17, issue 7, 1-19

Abstract: This paper presents the results of a comprehensive investigation into the comparative analysis and design optimization of ferrite-based surface permanent magnet vernier machines (SPMVMs). While SPMVMs boast a simple mechanical structure and enhanced torque density attributed to the flux modulation effect, they suffer from a persistent challenge of low power factor. Several factors hinder the adoption of low-cost ferrite magnets in SPMVMs. First, ferrite magnets are prone to irreversible demagnetization, constraining the allowable range of magnet thickness. Second, the reduced residual magnetic flux density of ferrite magnets exacerbates the decrease in power factor and machine efficiency. Thus, achieving optimal performance in ferrite-based SPMVMs necessitates the careful selection of various design parameters. To address these issues, this study employs a surrogate-based metaheuristic optimization algorithm with adaptive sampling to identify the optimal solution. Additionally, the integration of a Halbach array is explored to further enhance the performance of the three-slot/two-pole SPMVM topology. Subsequently, two ferrite-based SPMVM baseline models—one with a conventional SPM structure and another with a Halbach magnet array—are thoroughly designed, optimized, and subjected to detailed performance analysis using the 2D finite element method.

Keywords: design optimization; efficiency; ferrite; Halbach; magnetic saturation; power factor; PM vernier; torque density (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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