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- Title
Optimal Design of a Surface Permanent Magnet Machine for Electric Power Steering Systems in Electric Vehicle Applications Using a Gaussian Process-Based Approach.
- Authors
Choi, Gilsu; Jang, Gwan-Hui; Choi, Mingyu; Kang, Jungmoon; Kang, Ye Gu; Kim, Sehwan
- Abstract
The efficient design optimization of electric machines for electric power steering (EPS) applications poses challenges in meeting demanding performance criteria, including high power density, efficiency, and low vibration. Traditional optimization approaches often fail to find a global solution or suffer from excessive computation time. In response to the limitations of traditional approaches, this paper introduces a novel methodology by incorporating a Gaussian process-based adaptive sampling technique into a surrogate-assisted optimization process using a metaheuristic algorithm. Validation on a 72-slot/8-pole interior permanent magnet (IPM) machine demonstrates the superiority of the proposed approach, showcasing improved exploitation–exploration balance, faster convergence, and enhanced repeatability compared to conventional optimization methods. The proposed design process is then applied to two surface PM (SPM) machine configurations with 9-slot/6-pole and 12-slot/10-pole combinations for EPS applications. The results indicate that the 12-slot/10-pole SPM design surpasses the alternative design in torque density, efficiency, cogging torque, torque ripple, and manufacturability.
- Subjects
METAHEURISTIC algorithms; ELECTRIC metal-cutting; ELECTRIC machines; PERMANENT magnets; ELECTRIC vehicles; POWER density
- Publication
Actuators, 2024, Vol 13, Issue 1, p13
- ISSN
2076-0825
- Publication type
Article
- DOI
10.3390/act13010013