Abdul Shukor, Fairul Azhar and Abdulah, Norrimah and Raja Othman, Raja Nor Firdaus Kashfi and Che Ahmad, Suhairi Rizuan and Mohd Nasir, Nur Ashikin (2023) Modelling methods and structure topology of the switched reluctance synchronous motor type machine: A review. International Journal of Power Electronics and Drive Systems (IJPEDS, 14 (1). pp. 111-122. ISSN 2088-8694
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Abstract
The switched reluctance synchronous motors (SRSM) have been utilised as replacements for induction motors (IM) and permanent magnet synchronous motors (PMSM). The SRSM is a feasible solution for electric motors because of its robust and straightforward structure, resulting in low maintenance, manufacturing, and operating costs. However, the SRSM has several flaws, including low mean torque, low torque density and excessive torque ripples. The SRSM performance can be improved by considering the structure topology and driving system. This paper reviewed the performance characteristic of SRSM based on the structural topology. Several literature studies on the segmented structure topologies of SRSM were compared with the conventional structures. The performance of the SRSM can be estimated by using either numerical or analytical methods. The FEA and BEM are numerical techniques extensively used to optimise electrical motor performance. Although the numerical method can accurately estimate motor performance, the significant drawback is quite complicated, time-consuming, and difficult to implement the control algorithm with FEA software. However, the analytical method, especially the MEC method, is faster in evaluating motor performance and significantly reduces computational complexity, either with or without solving high-dimensional system matrices.
Item Type: | Article |
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Uncontrolled Keywords: | Analytical analysis, Electromagnetic analysis, Magnetic equivalent circuit, Mathematical modelling, Numerical analysis, Segmented structure, Switched reluctance motor |
Divisions: | Faculty of Electrical Engineering |
Depositing User: | Norfaradilla Idayu Ab. Ghafar |
Date Deposited: | 22 Jul 2024 16:41 |
Last Modified: | 22 Jul 2024 16:41 |
URI: | http://eprints.utem.edu.my/id/eprint/27424 |
Statistic Details: | View Download Statistic |
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