Access the full text.
Sign up today, get DeepDyve free for 14 days.
Purpose – 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. Design/methodology/approach – 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. Findings – 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. Originality/value – 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.
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering – Emerald Publishing
Published: Oct 28, 2014
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.