Application-Oriented System Level Optimization Method for Switched Reluctance Motor Drive Systems

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

Application-Oriented System Level Optimization Method for Switched Reluctance Motor Drive Systems

Diao, K Sun, X Lei, G

Guo, Y

Zhu, J

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: 2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia), 2021, 00, pp. 473-477
Issue Date:: 2021-03-09

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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	2020-11-29
dc.date.accessioned	2022-06-29T07:30:01Z
dc.date.available	2022-06-29T07:30:01Z
dc.date.issued	2021-03-09
dc.identifier.citation	2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia), 2021, 00, pp. 473-477
dc.identifier.isbn	978-1-7281-5301-8
dc.identifier.uri	http://hdl.handle.net/10453/158461
dc.description.abstract	This paper presents a novel application-oriented system level optimization method for switched reluctance motor (SRM) drive systems. First, the multiobjective optimization model is defined according to the design requirements. Then, all the parameters of the motor and controller are divided into three subspaces according to the sensitivity results on the defined objectives. Finally, the optimization of each subspace is performed sequentially by using the approximate models and advanced genetic algorithm, and the best solution can be selected from the Pareto optimal solutions. To verify the effectiveness of the proposed method, an SRM drive system with a segmented-rotor SRM and the angle position control method is investigated. This is a high-dimensional system level optimization problem with ten parameters. The computational cost can be greatly reduced without the sacrifice of accuracy. From the discussion, it can be found that the proposed multiobjective system level optimization method can achieve high efficiency and low torque ripple. Besides, it provides alternative solutions for applications with different output power demands.
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia)
dc.relation.ispartof	International Power Electronics and Motion Control Conference
dc.relation.ispartofseries	IEEE International Power Electronics and Motion Control Conference IPEMC
dc.relation.isbasedon	10.1109/ipemc-ecceasia48364.2020.9367987
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.title	Application-Oriented System Level Optimization Method for Switched Reluctance Motor Drive Systems
dc.type	Conference Proceeding
utslib.citation.volume	00
utslib.location.activity	Nanjing, China
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	2023-03-31T00:00:00+1000Z
dc.date.updated	2022-06-29T07:29:59Z
pubs.finish-date	2020-12-02
pubs.place-of-publication	USA
pubs.publication-status	Published
pubs.start-date	2020-11-29
pubs.volume	00
dc.location	USA

Abstract:

This paper presents a novel application-oriented system level optimization method for switched reluctance motor (SRM) drive systems. First, the multiobjective optimization model is defined according to the design requirements. Then, all the parameters of the motor and controller are divided into three subspaces according to the sensitivity results on the defined objectives. Finally, the optimization of each subspace is performed sequentially by using the approximate models and advanced genetic algorithm, and the best solution can be selected from the Pareto optimal solutions. To verify the effectiveness of the proposed method, an SRM drive system with a segmented-rotor SRM and the angle position control method is investigated. This is a high-dimensional system level optimization problem with ten parameters. The computational cost can be greatly reduced without the sacrifice of accuracy. From the discussion, it can be found that the proposed multiobjective system level optimization method can achieve high efficiency and low torque ripple. Besides, it provides alternative solutions for applications with different output power demands.

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http://hdl.handle.net/10453/158461