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Stefan cel Mare
University of Suceava
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Print ISSN: 1582-7445
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WorldCat: 643243560
doi: 10.4316/AECE


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  2/2023 - 2

GA and PSO Based Approaches for Fast Optimization of External Rotor Switched Reluctance Motor Design Parameters

POLAT, M. See more information about POLAT, M. on SCOPUS See more information about POLAT, M. on IEEExplore See more information about POLAT, M. on Web of Science, YILDIZ, A. See more information about YILDIZ, A. on SCOPUS See more information about YILDIZ, A. on SCOPUS See more information about YILDIZ, A. on Web of Science
 
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Download PDF pdficon (2,035 KB) | Citation | Downloads: 662 | Views: 954

Author keywords
electric vehicle, external rotor, switched reluctance motor, finite element analysis, heuristic optimization algorithm, optimization

References keywords
reluctance(25), switched(24), motor(20), optimization(17), design(13), torque(10), algorithm(10), electric(9), swarm(7), ripple(7)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2023-05-31
Volume 23, Issue 2, Year 2023, On page(s): 11 - 18
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.02002
Web of Science Accession Number: 001009953400002
SCOPUS ID: 85164329171

Abstract
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With the application of computational intelligence methods to different fields, it has also started to be used in the designs of electric motors. In this paper, a 3-phase 18/12 pole 30 kW in-wheel External Rotor Switched Reluctance Motor (ERSRM) is designed for the Electric Vehicles (EVs). For this design, an analytical model is developed using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. While determining the design dimensions of the ERSRM, it is aimed to obtain maximum efficiency and the desired torque fast in the developed models. As a result of the developed models using the GA and PSO methods, motor design parameters obtained are compared with the results of Finite Element Analysis (FEA). In the designed models, the inductance values at the unaligned and aligned positions, torque, and efficiency values are calculated. The results obtained from the heuristic based models developed are subjected to various error calculation methods. Consequently, it is observed that the results obtained by the GA and PSO methods are much faster than that of the FEA and the errors are acceptable. Besides, it is seen that the ERSRM design realized by the proposed methods has low time cost and high accuracy.


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References Weight

Web of Science® Citations for all references: 1,262 TCR
SCOPUS® Citations for all references: 1,869 TCR

Web of Science® Average Citations per reference: 35 ACR
SCOPUS® Average Citations per reference: 52 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-07-16 09:28 in 215 seconds.




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