Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm

Purpose The purpose of this paper is to investigate Halbach array effects in surface mounted permanent magnet machine (SMPM) in terms of both self-sensing and torque capabilities. A comparison between a conventional SMPM, which has radially magnetized rotor, and a Halbach machine has been carried...

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Main Authors: Caner, Murat, Gerada, Christopher, Asher, Greg, Özer, Tolga
Format: Article
Published: Emerald 2016
Subjects:
Online Access:https://eprints.nottingham.ac.uk/39281/
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author Caner, Murat
Gerada, Christopher
Asher, Greg
Özer, Tolga
author_facet Caner, Murat
Gerada, Christopher
Asher, Greg
Özer, Tolga
author_sort Caner, Murat
building Nottingham Research Data Repository
collection Online Access
description Purpose The purpose of this paper is to investigate Halbach array effects in surface mounted permanent magnet machine (SMPM) in terms of both self-sensing and torque capabilities. A comparison between a conventional SMPM, which has radially magnetized rotor, and a Halbach machine has been carried out. Design/methodology/approach The geometric parameters of the two machines have been optimized using genetic algorithm (GA) with looking Pareto. The performance of the machines’ geometry has been calculated by finite element analysis (FEA) software, and two parametric machine models have been realized in Matlab coupled with the FEA and GA toolboxes. Outer volume of the machine, thus copper loss per volume has been kept constant. The Pareto front approach, which simultaneously considers looks two aims, has been used to provide the trade-off between the torque and sensorless performances. Findings The two machines’ results have been compared separately for each loading condition. According to the results, the superiority of the Halbach machine has been shown in terms of sensorless capability compromising torque performance. Additionally, this paper shows that the self-sensing properties of a SMPM machine should be considered at the design stage of the machine. Originality/value A Halbach machine design optimization has been presented using Pareto optimal set which provides a trade-off comparison between two aims without using weightings. These are sensorless performance and torque capability. There is no such a work about sensorless capability of the Halbach type SMPM in the literature.
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publishDate 2016
publisher Emerald
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spelling nottingham-392812020-05-04T18:08:43Z https://eprints.nottingham.ac.uk/39281/ Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm Caner, Murat Gerada, Christopher Asher, Greg Özer, Tolga Purpose The purpose of this paper is to investigate Halbach array effects in surface mounted permanent magnet machine (SMPM) in terms of both self-sensing and torque capabilities. A comparison between a conventional SMPM, which has radially magnetized rotor, and a Halbach machine has been carried out. Design/methodology/approach The geometric parameters of the two machines have been optimized using genetic algorithm (GA) with looking Pareto. The performance of the machines’ geometry has been calculated by finite element analysis (FEA) software, and two parametric machine models have been realized in Matlab coupled with the FEA and GA toolboxes. Outer volume of the machine, thus copper loss per volume has been kept constant. The Pareto front approach, which simultaneously considers looks two aims, has been used to provide the trade-off between the torque and sensorless performances. Findings The two machines’ results have been compared separately for each loading condition. According to the results, the superiority of the Halbach machine has been shown in terms of sensorless capability compromising torque performance. Additionally, this paper shows that the self-sensing properties of a SMPM machine should be considered at the design stage of the machine. Originality/value A Halbach machine design optimization has been presented using Pareto optimal set which provides a trade-off comparison between two aims without using weightings. These are sensorless performance and torque capability. There is no such a work about sensorless capability of the Halbach type SMPM in the literature. Emerald 2016-09-30 Article PeerReviewed Caner, Murat, Gerada, Christopher, Asher, Greg and Özer, Tolga (2016) Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm. COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, 35 (5). pp. 1741-1759. ISSN 0332-1649 Design optimization Permanent magnet machine Sensorless control Genetic algorithm Halbach array Pareto front http://dx.doi.org/10.1108/COMPEL-06-2015-0218 doi:10.1108/COMPEL-06-2015-0218 doi:10.1108/COMPEL-06-2015-0218
spellingShingle Design optimization
Permanent magnet machine
Sensorless control
Genetic algorithm
Halbach array
Pareto front
Caner, Murat
Gerada, Christopher
Asher, Greg
Özer, Tolga
Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title_full Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title_fullStr Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title_full_unstemmed Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title_short Design optimization of Halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
title_sort design optimization of halbach array permanent magnet motor to achieve sensorless performance using genetic algorithm
topic Design optimization
Permanent magnet machine
Sensorless control
Genetic algorithm
Halbach array
Pareto front
url https://eprints.nottingham.ac.uk/39281/
https://eprints.nottingham.ac.uk/39281/
https://eprints.nottingham.ac.uk/39281/