Research on Torque Optimization of Outer Rotor Permanent Magnet Synchronous Motor Based on Response Surface Methodology

To optimize a 27-slot/24-pole outer-rotor permanent magnet synchronous motor (ORPMSM) for improved average output torque and reduced torque ripple, a torque optimization method based on response surface methodology (RSM) is proposed. The stator slot opening width, pole-arc coefficient, and permanent magnet thickness are selected as the key structural optimization variables. Through finite element analysis (FEA), a response surface model function is employed to perform regression fitting for different variable combinations. With the objectives of maximizing average output torque and minimizing torque ripple, a multi-objective optimization is conducted, yielding an optimal parameter solution. The results demonstrate that the RSM-based optimization method effectively enhances the motor's average output torque while reducing torque ripple, validating both the rationality of the RSM approach and the accuracy of the FEA simulations.

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Publication Details

Published
2025-04-25
DOI
https://doi.org/10.1109/iccea65460.2025.11102460
Primary Topic
Metallurgy and Material Forming
Type
article
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article

Research on Torque Optimization of Outer Rotor Permanent Magnet Synchronous Motor Based on Response Surface Methodology

Wenchen Li, Baowang Huang, Ping Huo
Metallurgy and Material Forming
article

Research on Torque Optimization of Outer Rotor Permanent Magnet Synchronous Motor Based on Response Surface Methodology

Wenchen Li, Baowang Huang, Ping Huo
article en

Abstract

To optimize a 27-slot/24-pole outer-rotor permanent magnet synchronous motor (ORPMSM) for improved average output torque and reduced torque ripple, a torque optimization method based on response surface methodology (RSM) is proposed. The stator slot opening width, pole-arc coefficient, and permanent magnet thickness are selected as the key structural optimization variables. Through finite element analysis (FEA), a response surface model function is employed to perform regression fitting for different variable combinations. With the objectives of maximizing average output torque and minimizing torque ripple, a multi-objective optimization is conducted, yielding an optimal parameter solution. The results demonstrate that the RSM-based optimization method effectively enhances the motor's average output torque while reducing torque ripple, validating both the rationality of the RSM approach and the accuracy of the FEA simulations.

North China University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 77%
Metallurgy and Material Forming
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