Design optimization and analysis of switched reluctance motor using genetic algorithm optimization technique

This paper presents efficiency optimization of switched reluctance motor based on genetic algorithm optimization technique. Switched reluctance motor (SRM) is considered for various applications due to its simple and robust construction. It is very essential to improve efficiency of switched relucta...

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Published inTESEA, transactions on energy systems and engineering applications Vol. 6; no. 1; pp. 1 - 13
Main Author N. Patel, Amit
Format Journal Article
LanguageEnglish
Published Universidad Tecnologica de Bolivar 26.02.2025
Subjects
Design Optimization
Finite Element Analysis
Genetic Algorithms
Parametric Analysis
Switched Reluctance Motor
Online AccessGet full text
ISSN2745-0120
2745-0120
DOI10.32397/tesea.vol6.n1.659

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Abstract This paper presents efficiency optimization of switched reluctance motor based on genetic algorithm optimization technique. Switched reluctance motor (SRM) is considered for various applications due to its simple and robust construction. It is very essential to improve efficiency of switched reluctance motor. In this paper, optimization of 8/6 switched reluctance motor is achieved by using genetic algorithm with efficiency as its objective function. The objective of the paper is to identify the best switched reluctance motor design that provides better efficiency to satisfy the unique requirements of various applications. Using finite element analysis, a design validation of motor and characterization was made. It is analyzed that analytical results and simulation results are very close which establishes correctness of designs. The optimization result shows that the newly developed SRM design achieved better efficiency. The efficiency is increased from 82.75 % to 86.19 % with minor increase in weight. Improvement in efficiency can lead to lower energy usage, longer motor life span, and better performance.
AbstractList This paper presents efficiency optimization of switched reluctance motor based on genetic algorithm optimization technique. Switched reluctance motor (SRM) is considered for various applications due to its simple and robust construction. It is very essential to improve efficiency of switched reluctance motor. In this paper, optimization of 8/6 switched reluctance motor is achieved by using genetic algorithm with efficiency as its objective function. The objective of the paper is to identify the best switched reluctance motor design that provides better efficiency to satisfy the unique requirements of various applications. Using finite element analysis, a design validation of motor and characterization was made. It is analyzed that analytical results and simulation results are very close which establishes correctness of designs. The optimization result shows that the newly developed SRM design achieved better efficiency. The efficiency is increased from 82.75 % to 86.19 % with minor increase in weight. Improvement in efficiency can lead to lower energy usage, longer motor life span, and better performance.
Author N. Patel, Amit
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Cites_doi 10.1016/j.enconman.2021.114336
10.1109/ICElMach.2012.6349846
10.1007/s11042-020-10139-6
10.1109/PEDSTC53976.2022.9767476
10.2528/PIER13040705
10.1109/IECON.2005.1569169
10.1109/TIA.2002.805571
10.1063/1.1452667
10.1109/ACCESS.2020.2993235
10.1016/j.rser.2019.109384
10.1109/JPROC.2006.892482
10.1109/ACCESS.2018.2837111
10.1109/ICElMach.2012.6349853
10.1504/IJEHV.2018.098121
10.1109/28.464522
10.1109/TIE.2010.2051390
10.1109/TMAG.2003.816248
10.1109/28.2896
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ref15
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ref16
ref19
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ref8
ref7
ref9
ref4
ref3
ref6
ref5
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SubjectTerms Design Optimization
Finite Element Analysis
Genetic Algorithms
Parametric Analysis
Switched Reluctance Motor
Title Design optimization and analysis of switched reluctance motor using genetic algorithm optimization technique
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