System-Level Robust Design Optimization of a Switched Reluctance Motor Drive System Considering Multiple Driving Cycles

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

System-Level Robust Design Optimization of a Switched Reluctance Motor Drive System Considering Multiple Driving Cycles

Diao, K Sun, X Lei, G

Bramerdorfer, G Guo, Y

Zhu, J

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Transactions on Energy Conversion, 2021, 36, (1), pp. 348-357
Issue Date:: 2021-03-01

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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	Bramerdorfer, G
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	2022-01-30T09:39:44Z
dc.date.available	2022-01-30T09:39:44Z
dc.date.issued	2021-03-01
dc.identifier.citation	IEEE Transactions on Energy Conversion, 2021, 36, (1), pp. 348-357
dc.identifier.issn	0885-8969
dc.identifier.issn	1558-0059
dc.identifier.uri	http://hdl.handle.net/10453/153870
dc.description.abstract	In this article, a novel system-level robust design optimization method is presented to improve the performance of switched reluctance motor (SRM) drive systems under multiple operating conditions. Based on typical driving cycles of electric vehicles (EVs), five typical driving modes of the SRM are determined. The optimization objectives in each driving mode are established. The significant parameters of the motor and controller of each driving mode are selected as the optimization variables by using the sensitivity analysis. In order to simplify the optimization process, correlation analysis is performed to determine the coherence of the objective functions of all driving modes. Then, a sequential Taguchi method is applied to find an optimal design which is less sensitive to the noise factors. To verify the effectiveness of the proposed method, an SRM drive system applied in EVs with a 12/10 SRM and angle position control method is investigated. It is found that the proposed method can significantly reduce the torque ripple and improve the comprehensive performance. Finally, a 12/10 SRM is prototyped and tested to validate the simulation results.
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 Energy Conversion
dc.relation.isbasedon	10.1109/TEC.2020.3009408
dc.rights	info:eu-repo/semantics/embargoedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	Electrical & Electronic Engineering
dc.title	System-Level Robust Design Optimization of a Switched Reluctance Motor Drive System Considering Multiple Driving Cycles
dc.type	Journal Article
utslib.citation.volume	36
utslib.for	0906 Electrical and Electronic 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	*
utslib.copyright.embargo	2023-03-31T00:00:00+1000Z
dc.date.updated	2022-01-30T09:39:39Z
pubs.issue	1
pubs.publication-status	Published
pubs.volume	36
utslib.citation.issue	1

Abstract:

In this article, a novel system-level robust design optimization method is presented to improve the performance of switched reluctance motor (SRM) drive systems under multiple operating conditions. Based on typical driving cycles of electric vehicles (EVs), five typical driving modes of the SRM are determined. The optimization objectives in each driving mode are established. The significant parameters of the motor and controller of each driving mode are selected as the optimization variables by using the sensitivity analysis. In order to simplify the optimization process, correlation analysis is performed to determine the coherence of the objective functions of all driving modes. Then, a sequential Taguchi method is applied to find an optimal design which is less sensitive to the noise factors. To verify the effectiveness of the proposed method, an SRM drive system applied in EVs with a 12/10 SRM and angle position control method is investigated. It is found that the proposed method can significantly reduce the torque ripple and improve the comprehensive performance. Finally, a 12/10 SRM is prototyped and tested to validate the simulation results.

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http://hdl.handle.net/10453/153870