LAPSE:2023.12995
Published Article
LAPSE:2023.12995
Multi-Objective Optimization Design and Analysis of V-Shape Permanent Magnet Synchronous Motor
Sheng-Ching Wang, Yu-Cheng Nien, San-Ming Huang
February 28, 2023
Abstract
Permanent magnet synchronous motors (PMSMs) are the main source of power in modern machine tools and are required to generate a high torque over a wide speed range in order to improve manufacturing efficiency. This study sets out to optimize the rotor design of a PMSM with a rated power, rated speed, rated torque and maximum speed of 34 kW, 2250 rpm, 144.3 N·m and 11,250 rpm, respectively. A multi-objective optimization algorithm is employed to determine the rotor design parameters which maximize the output torque of the PMSM over three different load conditions (no load, rated load and maximum speed load). ANSYS multi-physics simulations are conducted to examine the electromagnetic, the structural field, temperature/flow field, demagnetization parament analysis and map analysis of global characteristics of the optimized PMSM. In general, the results show that the optimized PMSM provides a high torque and high-speed expansion performance, and thus facilitates a wide range of applications from low-speed heavy cutting to high-speed cutting without the need to replace the motor or machine tool.
Keywords
multi-objective optimization, multi-physics analysis, permanent magnet synchronous motor
Suggested Citation
Wang SC, Nien YC, Huang SM. Multi-Objective Optimization Design and Analysis of V-Shape Permanent Magnet Synchronous Motor. (2023). LAPSE:2023.12995
Author Affiliations
Wang SC: Department of Mechanical Engineering, National United University, Miaoli 360302, Taiwan
Nien YC: Department of Mechanical Engineering, National United University, Miaoli 360302, Taiwan
Huang SM: Department of Mechanical Engineering, National United University, Miaoli 360302, Taiwan
Journal Name
Energies
Volume
15
Issue
10
First Page
3496
Year
2022
Publication Date
2022-05-10
ISSN
1996-1073
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Original Submission
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PII: en15103496, Publication Type: Journal Article
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LAPSE:2023.12995
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https://doi.org/10.3390/en15103496
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