Vector Modulation-Based Model Predictive Current Control with Filter Resonance Suppression and Zero-Current Switching Sequence for Two-Stage Matrix Converter

Zhengfei Di, Demin Xu and Kehan Zhang
Additional contact information
Zhengfei Di: State Key Laboratory of Underwater Information and Control, Northwestern Polytechnical University, Xi’an 710072, China
Demin Xu: State Key Laboratory of Underwater Information and Control, Northwestern Polytechnical University, Xi’an 710072, China
Kehan Zhang: State Key Laboratory of Underwater Information and Control, Northwestern Polytechnical University, Xi’an 710072, China

Energies, 2021, vol. 14, issue 12, 1-21

Abstract: This paper proposes a novel model predictive current control scheme for two-stage matrix converter. The switching frequency is kept constant by fixing the switching instant. The control strategy achieves to control source reactive power in the input side and output currents in the output side. In addition, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, a zero-current switching sequence is proposed and implemented to insure zero-current switching operations and reduce the switching losses. Furthermore, in order to suppress the input filter resonance, which is easier to be inspired by the model predictive control, compared with traditional control strategies, an innovative active damping technique is proposed and implemented. Finally, both simulation and experiment are implemented to verify the performance of the proposed strategy. The results demonstrate that the control system features both good steady and transient performance.

Keywords: two-stage matrix converter; model predictive control; vector synthesis; zero-current switching strategy; input filter resonance suppression (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/12/3685/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/12/3685/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:12:p:3685-:d:578690

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().