Publication:
Optimal design of SMPMSM using Genetic Algorithm based on Finite Element Model
Optimal design of SMPMSM using Genetic Algorithm based on Finite Element Model
Date
2022-01-01
Authors
Mohd-Shafri S.A.
Tiang Tow Leong
Ishak D.
Tan C.J.
Mohd Saufi Ahmad
Leong J.H.
Ong Hui Lin
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Science and Business Media Deutschland GmbH
Research Projects
Organizational Units
Journal Issue
Abstract
This paper deals with an optimal design of a surface-mounted permanent magnet synchronous machine (SMPMSM) using a genetic algorithm (GA) method. To analyze the characteristic of permanent magnet (PM) motors, the classical optimization method, such as the finite element method (FEM), is intensively used. In this design, a three-phase 12-slot/8-pole PM motor is established with FEM with radial magnetization pattern. Then, the GA is used to search the optimality of SMPMSM machine design. In the final analysis, the optimal new design of SMPMSM is demonstrated by comparing it with the initial design that is investigated by FEM. The result of induced back-EMF, total harmonic distortion, and magnetic flux density of optimal design are compared with the initial design to show the advantages of GA optimization method.
Description
Keywords
Finite element,
Genetic algorithm,
Optimal design,
Permanent magnet synchronous machine,
Surface-mounted