Efficiency improvement and torque ripple minimization of Switched Reluctance Motor using FEM and Seeker Optimization Algorithm

• This paper proposes a new method to optimize a Switched Reluctance Motor (SRM).
• A combination of SOA and GA with Finite Element Method (FEM) analysis is employed to solve the SRM design optimization.
• The results show that optimized SRM obtains higher average torque and higher efficiency.

In this paper, performance optimization of Switched Reluctance Motor (SRM) was determined using Seeker Optimization Algorithm (SOA). The most efficient aim of the algorithm was found for maximum torque value at a minimum mass of the entire construction, following changing the geometric parameters. The optimization process was carried out using a combination of Seeker Optimization Algorithm and Finite Element Method (FEM). Fitness value was calculated by FEM analysis using COMSOL3.4, and the SOA was realized by MATLAB. The proposed method has been applied for a case study and it has been also compared with Genetic Algorithm (GA). The results show that the optimized motor using SOA had higher torque value and efficiency with lower mass and torque ripple, exhibiting the validity of this methodology for SRM design.