Model Predictive Control with Series Structure for Five-phase PMSHM Based on Discrete Space Virtual Voltage Modulation

Li, K; Zha, X; Sun, X; Lei, G

Model Predictive Control with Series Structure for Five-phase PMSHM Based on Discrete Space Virtual Voltage Modulation

Li, K Zha, X Sun, X Lei, G

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Publisher:: Institute of Electrical and Electronics Engineers (IEEE)
Publication Type:: Journal Article
Citation:: IEEE Transactions on Transportation Electrification, 2024, PP, (99), pp. 1-1
Issue Date:: 2024-01-01

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Field	Value	Language
dc.contributor.author	Li, K
dc.contributor.author	Zha, X
dc.contributor.author	Sun, X
dc.contributor.author	Lei, G https://orcid.org/0000-0002-8369-6802
dc.date.accessioned	2024-08-07T05:37:34Z
dc.date.available	2024-08-07T05:37:34Z
dc.date.issued	2024-01-01
dc.identifier.citation	IEEE Transactions on Transportation Electrification, 2024, PP, (99), pp. 1-1
dc.identifier.issn	2332-7782
dc.identifier.issn	2332-7782
dc.identifier.uri	http://hdl.handle.net/10453/180335
dc.description.abstract	This paper proposes a novel two-stage series model predictive control (MPC) method using discrete space virtual voltage modulation (DSVVM) for five-phase permanent magnet synchronous hub motors. The proposed control method is applied to optimize two control periods. First, the usage of DSVVM reduces harmonic currents in the harmonic plane while minimizing current tracking errors in the primary plane. Second, the simplified prediction vector selection strategy is designed to select the candidate prediction vectors to avoid the increasing computational burden caused by DSVVM. Third, the first-stage prediction results are extrapolated at the second prediction step to ensure the best control effect during the two control periods while using the same virtual vector. Additionally, the proposed switching pattern of double virtual vectors ensures minimal transitions during the two control periods. Finally, Comparative experiments conducted on a DSP between the proposed approach and the conventional MPC methods are conducted to verify the effectiveness of the proposed method.
dc.language	en
dc.publisher	Institute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartof	IEEE Transactions on Transportation Electrification
dc.relation.isbasedon	10.1109/TTE.2024.3403678
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	0906 Electrical and Electronic Engineering
dc.subject.classification	4008 Electrical engineering
dc.title	Model Predictive Control with Series Structure for Five-phase PMSHM Based on Discrete Space Virtual Voltage Modulation
dc.type	Journal Article
utslib.citation.volume	PP
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/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	recently_added	*
dc.date.updated	2024-08-07T05:37:32Z
pubs.issue	99
pubs.publication-status	Published
pubs.volume	PP
utslib.citation.issue	99

Abstract:

This paper proposes a novel two-stage series model predictive control (MPC) method using discrete space virtual voltage modulation (DSVVM) for five-phase permanent magnet synchronous hub motors. The proposed control method is applied to optimize two control periods. First, the usage of DSVVM reduces harmonic currents in the harmonic plane while minimizing current tracking errors in the primary plane. Second, the simplified prediction vector selection strategy is designed to select the candidate prediction vectors to avoid the increasing computational burden caused by DSVVM. Third, the first-stage prediction results are extrapolated at the second prediction step to ensure the best control effect during the two control periods while using the same virtual vector. Additionally, the proposed switching pattern of double virtual vectors ensures minimal transitions during the two control periods. Finally, Comparative experiments conducted on a DSP between the proposed approach and the conventional MPC methods are conducted to verify the effectiveness of the proposed method.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/180335