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Optimal Design of Switched Reluctance Motor Using PSO Based FEM-EMC Modeling

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 5 No. 5 (2015)

DOI
10.11591/ijece.v5i5.pp887-895
ISSN
2088-8708, 2088-8708
Published
2015-10-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

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.

Collaboration network of the authors

10 authors · 16 co-authorship links

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • University Frères Mentouri Constantine 1
  • Affiliation unknown
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Abdelmalek BoulahiaUniversity Frères Mentouri Constantine 12
Adel MehdiUniversity Frères Mentouri Constantine 12
K. NabtiAffiliation unknown1
Salah Eddine RezguiUniversity Frères Mentouri Constantine 11
Houssam Eddine MedouceUniversity Frères Mentouri Constantine 11
Tariq BenamimourUniversity Frères Mentouri Constantine 11
Hind DjeghloudUniversity Frères Mentouri Constantine 11

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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