LAPSE:2023.18270
Published Article
LAPSE:2023.18270
Multi-Virtual-Vector Model Predictive Current Control for Dual Three-Phase PMSM
Tianjiao Luan, Zhichao Wang, Yang Long, Zhen Zhang, Qi Li, Zhihao Zhu, Chunhua Liu
March 7, 2023
This paper proposes a multi-virtual-vector model predictive control (MPC) for a dual three-phase permanent magnet synchronous machine (DTP-PMSM), which aims to regulate the currents in both fundamental and harmonic subspace. Apart from the fundamental α-β subspace, the harmonic subspace termed x-y is decoupled in multiphase PMSM according to vector space decomposition (VSD). Hence, the regulation of x-y currents is of paramount importance to improve control performance. In order to take into account both fundamental and harmonic subspaces, this paper presents a multi-virtual-vector model predictive control (MVV-MPC) scheme to significantly improve the steady performance without affecting the dynamic response. In this way, virtual vectors are pre-synthesized to eliminate the components in the x-y subspace and then a vector with adjustable phase and amplitude is composed of two effective virtual vectors and a zero vector. As a result, an enhanced current tracking ability is acquired due to the expanded output range of the voltage vector. Lastly, both simulation and experimental results are given to confirm the feasibility of the proposed MVV-MPC for DTP-PMSM.
Keywords
Model Predictive Control, multiphase electric drives, PMSM
Suggested Citation
Luan T, Wang Z, Long Y, Zhang Z, Li Q, Zhu Z, Liu C. Multi-Virtual-Vector Model Predictive Current Control for Dual Three-Phase PMSM. (2023). LAPSE:2023.18270
Author Affiliations
Luan T: China Academy of Launch Vehicle Technology, Beijing 100076, China
Wang Z: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China [ORCID]
Long Y: Jiangxi Water Resources Institute, Nanchang 330044, China
Zhang Z: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Li Q: School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Zhu Z: School of Electrical Engineering, Nantong University, Nantong 226019, China
Liu C: School of Energy and Environment, City University of Hong Kong, Hong Kong, China [ORCID]
Journal Name
Energies
Volume
14
Issue
21
First Page
7292
Year
2021
Publication Date
2021-11-03
Published Version
ISSN
1996-1073
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PII: en14217292, Publication Type: Journal Article
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LAPSE:2023.18270
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doi:10.3390/en14217292
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