LAPSE:2023.21958
Published Article
LAPSE:2023.21958
Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm
Łukasz Knypiński, Karol Pawełoszek, Yvonnick Le Menach
March 23, 2023
Abstract
The paper presents the optimization method and computer software for the design of a low-power line-start permanent magnet synchronous motor (LSPMSM). The in-house-developed computer software was created with two independent modules: (a) the optimization procedure and (b) the numerical model of the motor. The optimization procedure used was a metaheuristic optimization method based on the gray wolf algorithm. Four design variables linked to the rotor structure were selected. The optimization process was performed from the rotor of a low-power induction motor (IM). The prototype of the motor (LSPMSM) was then built. The experimental measurements were performed for base the IM and optimized LSPMSM. The results of the measurements were compared for both motors. The experimental results confirmed the better performance of the designed motor in comparison to the induction motor.
Keywords
efficiency, gray wolf optimization method, line-start permanent magnet synchronous motor, metaheuritsic algorithm, optimal design
Subject
Suggested Citation
Knypiński Ł, Pawełoszek K, Le Menach Y. Optimization of Low-Power Line-Start PM Motor Using Gray Wolf Metaheuristic Algorithm. (2023). LAPSE:2023.21958
Author Affiliations
Knypiński Ł: Institute of Electrical Engineering and Electronics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznań, Poland [ORCID]
Pawełoszek K: Institute of Electrical Engineering and Electronics, Poznan University of Technology, Piotrowo 3A, 60-965 Poznań, Poland
Le Menach Y: Laboratory of Electrical Engineering and Power Electronics (L2EP), University of Lille, Bât. ESPRIT, 59655 Villeneuve d’Ascq, France
Journal Name
Energies
Volume
13
Issue
5
Article Number
E1186
Year
2020
Publication Date
2020-03-05
ISSN
1996-1073
Version Comments
Original Submission
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PII: en13051186, Publication Type: Journal Article
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LAPSE:2023.21958
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https://doi.org/10.3390/en13051186
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