Open AccessOptimal Design of Switched Reluctance Motor Using PSO Based FEM-EMC Modeling
Author(s) -
Mouellef Sihem,
A. Bentounsi,
H. Benalla
Publication year - 2015
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v5i5.pp887-895
Subject(s) - switched reluctance motor , torque ripple , particle swarm optimization , finite element method , matlab , torque , stator , rotor (electric) , computer science , control theory (sociology) , torque density , electromagnetic coil , genetic algorithm , optimal design , induction motor , direct torque control , engineering , physics , mechanical engineering , algorithm , structural engineering , electrical engineering , control (management) , voltage , artificial intelligence , machine learning , thermodynamics , operating system
This paper aims to optimize the design of a prototype of a 6/4 Switched Reluctance Motor (SRM) using the Particle Swarm Optimization (PSO) algorithm. The geometrical parameters to optimize are the widths of the stator and rotor teeth due to their significant effects on the prototype design and the performances in terms of increased average torque and reduced torque ripple. The studied 3kW SRM is modeled using a numerical-analytical approach based on a coupled Finite Element Method with Equivalent Magnetic Circuit (FEM-EMC). The simulations are performed under MATLAB environment with user-friendly software. The optimal results found are discussed, compared against those obtained by the Genetic Algorithms (GA) and showed a significant improvement in average torque.