Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there...

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Autores principales:	Cvetkovski Goga Vladimir, Petkovska Lidija
Formato:	article
Lenguaje:	EN
Publicado:	Sciendo 2021
Materias:	permanent magnet synchronous motor optimisation methods cogging torque genetic algorithm finite element method Electronics TK7800-8360
Acceso en línea:	https://doaj.org/article/e6a099f1fd1645d7bb539cf5db07b077
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id	oai:doaj.org-article:e6a099f1fd1645d7bb539cf5db07b077
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spelling	oai:doaj.org-article:e6a099f1fd1645d7bb539cf5db07b0772021-12-05T14:11:09ZSelected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation2543-429210.2478/pead-2021-0012https://doaj.org/article/e6a099f1fd1645d7bb539cf5db07b0772021-01-01T00:00:00Zhttps://doi.org/10.2478/pead-2021-0012https://doaj.org/toc/2543-4292Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimisation of the ripple of this torque in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variety of many geometrical motor parameters. In this research work, a novel approach will be introduced where two different nature-inspired algorithms, such as genetic algorithm (GA) and cuckoo search (CS) algorithm are used as an optimisation tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For a detailed analysis of the three different motor models, the initial motor and the two optimised motor models are modelled and analysed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.Cvetkovski Goga VladimirPetkovska LidijaSciendoarticlepermanent magnet synchronous motoroptimisation methodscogging torquegenetic algorithmfinite element methodElectronicsTK7800-8360ENPower Electronics and Drives, Vol 6, Iss 1, Pp 209-222 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	permanent magnet synchronous motor optimisation methods cogging torque genetic algorithm finite element method Electronics TK7800-8360
spellingShingle	permanent magnet synchronous motor optimisation methods cogging torque genetic algorithm finite element method Electronics TK7800-8360 Cvetkovski Goga Vladimir Petkovska Lidija Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
description	Both permanent magnet brushless DC motors and permanent magnet synchronous motors have attracted wide attention and are increasingly used in industrial high-performance applications in recent years. Those motors are known for their good electrical, magnetic and performance characteristics, but there is one parameter known as cogging torque that has a negative influence on the performance characteristics of the motor. This pulsating torque is generated as a result of the interaction between the stator teeth and the permanent magnets. The minimisation of the ripple of this torque in those permanent magnet motors is of great importance and is generally achieved by a special motor design which in the design process involves a variety of many geometrical motor parameters. In this research work, a novel approach will be introduced where two different nature-inspired algorithms, such as genetic algorithm (GA) and cuckoo search (CS) algorithm are used as an optimisation tool, in which the defined equation for the maximum value of the cogging torque is applied as an objective function. Therefore, a proper mathematical presentation of the maximum value of the cogging torque for the analysed synchronous motor is developed and implemented in the research work. For a detailed analysis of the three different motor models, the initial motor and the two optimised motor models are modelled and analysed using a finite element method approach. The cogging torque is analytically and numerically calculated and the results for all the models are presented.
format	article
author	Cvetkovski Goga Vladimir Petkovska Lidija
author_facet	Cvetkovski Goga Vladimir Petkovska Lidija
author_sort	Cvetkovski Goga Vladimir
title	Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
title_short	Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
title_full	Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
title_fullStr	Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
title_full_unstemmed	Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation
title_sort	selected nature-inspired algorithms in function of pm synchronous motor cogging torque minimisation
publisher	Sciendo
publishDate	2021
url	https://doaj.org/article/e6a099f1fd1645d7bb539cf5db07b077
work_keys_str_mv	AT cvetkovskigogavladimir selectednatureinspiredalgorithmsinfunctionofpmsynchronousmotorcoggingtorqueminimisation AT petkovskalidija selectednatureinspiredalgorithmsinfunctionofpmsynchronousmotorcoggingtorqueminimisation
_version_	1718371330434269184

Selected Nature-Inspired Algorithms in Function of PM Synchronous Motor Cogging Torque Minimisation

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