Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/26302
Title: Optimal design of single phase permanent magnet brushless DC motor using particle swarm optimisation
Authors: Cvetkovski, Goga
Petkovska, Lidija
Lefley, Paul
Keywords: finite element method, design optimization, swarm inteligence, permanent magnet motor, brushless motor
Issue Date: 28-Oct-2014
Publisher: Emerald
Source: Cvetkovski, G., Petkovska, L. and Lefley, P. (2014), "Optimal design of single phase permanent magnet brushless DC motor using particle swarm optimisation", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 33 No. 6, pp. 1863-1876. https://doi.org/10.1108/COMPEL-11-2013-0379
Journal: COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
Abstract: The purpose of this paper is to perform an optimal design of single phase permanent magnet brushless DC motor (SPBLDCM) using efficiency of the motor as objective function. In the design procedure performed on SPBLDCM, particle swarm optimisation (PSO) as an optimisation tool is used. The created computer programme for optimal design of electrical machines is based on the PSO. According to the design characteristics of SPBLDCM, some of the motor parameters are chosen to be constant and others variable. A comparative analysis of both motor models based on the value of the objective function, as well as the values of the optimisation parameters, is performed. From the comparative data analysis of both motor models, it can be concluded that the main objective of the optimisation is realised, and it is achieved by an improvement of the efficiency of the motor. An optimisation technique based on PSO has been developed and applied to the design of SPBLDCM. According to the results it can be concluded that the PSO is a very suitable tool for design optimisation of SPBLDCM and electromagnetic devices in general. The quality of the PSO model has been proved through the data analysis of the prototype and optimised solution. At the end, the quality of the PSO solution has been again proved by comparative analysis of the two motor models using FEM as a performance analysis tool.
URI: http://hdl.handle.net/20.500.12188/26302
DOI: 10.1108/compel-11-2013-0379
Appears in Collections:Faculty of Electrical Engineering and Information Technologies: Journal Articles

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