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

• Published in: TESEA, transactions on energy systems and engineering applications Vol. 6; no. 1; pp. 1 - 13
• Main Author: N. Patel, Amit
• Format: Journal Article
• Language: English
• Published: Universidad Tecnologica de Bolivar 26.02.2025
• Subjects: Design Optimization; Finite Element Analysis; Genetic Algorithms; Parametric Analysis; Switched Reluctance Motor
• ISSN: 2745-0120; 2745-0120
• DOI: 10.32397/tesea.vol6.n1.659

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.