Volume 21 No 7 (2023)
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PMSM Design and Optimization using Electro-magnetic Analysis with Genetic Algorithm (GA) Approach
Moussa KHELIFA, Khadidja BOUALI
Abstract
PMSMs have emerged as a popular choice in numerous industrial applications due to their exceptional efficiency, easy rotor manufacturing and simple structure, and precise control. However, achieving an optimal motor design that satisfies diverse performance criteria remains a challenging task. Cogging torque is a critical issue in PMSMs, as it can cause undesirable vibration and noise, leading to reduced efficiency and performance. Additionally, optimizing flux density is crucial to enhance the overall motor efficiency and power density. This paper presents a comprehensive investigation into the design and optimization of Permanent Magnet Synchronous Motors (PMSMs) focusing on three critical parameters: magnet Embrace and magnet Offset. The study employs electromagnetic analysis in combination with the Genetic Algorithm (GA) approach to achieve an optimal PMSM design, maximizing performance efficiency and torque output. The presented findings demonstrate the efficacy of employing electromagnetic analysis with the GA approach to optimize pole embrace and pole offset, in PMSM design. The results demonstrate that the proposed GA method provides superior solutions, leading to PMSMs with significantly reduced cogging torque and improved flux density, thus enhancing overall motor performance. The research results offer valuable insights for researchers and engineers in the electric machine and drive systems domain, facilitating the development of high-performance PMSMs for diverse applications, including electric vehicles, robotics, renewable energy systems, and industrial automation.
Keywords
PMSM; Design; Optimization; Genetic Algorithms; Electromagnetic Analyses.
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