Multiobjective system level optimization method for switched reluctance motor drive systems using finite-element model

Diao, K; Sun, X; Lei, G; Guo, Y; Zhu, J

Multiobjective system level optimization method for switched reluctance motor drive systems using finite-element model

Diao, K Sun, X Lei, G

Guo, Y

Zhu, J

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Industrial Electronics, 2020, 67, (12), pp. 10055-10064
Issue Date:: 2020-12-01

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Field	Value	Language
dc.contributor.author	Diao, K
dc.contributor.author	Sun, X
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802
dc.contributor.author	Guo, Y https://orcid.org/0000-0001-6182-0684
dc.contributor.author	Zhu, J https://orcid.org/0000-0002-9763-4047
dc.date.accessioned	2021-03-11T00:44:42Z
dc.date.available	2021-03-11T00:44:42Z
dc.date.issued	2020-12-01
dc.identifier.citation	IEEE Transactions on Industrial Electronics, 2020, 67, (12), pp. 10055-10064
dc.identifier.issn	0278-0046
dc.identifier.issn	1557-9948
dc.identifier.uri	http://hdl.handle.net/10453/147017
dc.description.abstract	© 1982-2012 IEEE. This article presents a novel multiobjective system level optimization method to achieve the best performance of switched reluctance motor (SRM) drive systems. First, the multiobjective optimization problem for the SRM drive systems is defined. Then, all parameters of the drive systems, including the motor level and control level, are divided into three subspaces according to their influences on the objectives. Finally, the optimization of each subspace is performed sequentially until a convergence criterion is met. Then, the optimal solution can be chosen from the Pareto solutions according to a selection criterion. Meanwhile, the sensitivity analysis, the approximate models, and the genetic algorithm are employed to reduce the computation cost. To verify the effectiveness of the proposed method, an SRM drive system with a segmented-rotor SRM (SSRM) and the angle position control method is investigated. This is a high-dimensional system level optimization problem with ten parameters. The finite-element model (FEM) results are verified by the experiment results. The optimal solution has been listed and verified by the FEM. From the discussion, it can be found that the proposed optimization method is efficient and optimized SSRM drive system has high efficiency and low torque ripple.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation	http://purl.org/au-research/grants/arc/DP0773858
dc.relation	University of Technology SydneyUTSCG09
dc.relation	Department of Innovation, Industry, Science and Research (Previously known as DEST)
dc.relation.ispartof	IEEE Transactions on Industrial Electronics
dc.relation.isbasedon	10.1109/TIE.2019.2962483
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering
dc.subject.classification	Electrical & Electronic Engineering
dc.title	Multiobjective system level optimization method for switched reluctance motor drive systems using finite-element model
dc.type	Journal Article
utslib.citation.volume	67
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - CCET - Centre for Clean Energy Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	open_access	*
pubs.consider-herdc	false
utslib.copyright.embargo	2022-12-01T00:00:00+1000Z
dc.date.updated	2021-03-11T00:44:40Z
pubs.issue	12
pubs.publication-status	Published
pubs.volume	67
utslib.citation.issue	12

Abstract:

© 1982-2012 IEEE. This article presents a novel multiobjective system level optimization method to achieve the best performance of switched reluctance motor (SRM) drive systems. First, the multiobjective optimization problem for the SRM drive systems is defined. Then, all parameters of the drive systems, including the motor level and control level, are divided into three subspaces according to their influences on the objectives. Finally, the optimization of each subspace is performed sequentially until a convergence criterion is met. Then, the optimal solution can be chosen from the Pareto solutions according to a selection criterion. Meanwhile, the sensitivity analysis, the approximate models, and the genetic algorithm are employed to reduce the computation cost. To verify the effectiveness of the proposed method, an SRM drive system with a segmented-rotor SRM (SSRM) and the angle position control method is investigated. This is a high-dimensional system level optimization problem with ten parameters. The finite-element model (FEM) results are verified by the experiment results. The optimal solution has been listed and verified by the FEM. From the discussion, it can be found that the proposed optimization method is efficient and optimized SSRM drive system has high efficiency and low torque ripple.

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http://hdl.handle.net/10453/147017