An Improved Finite-Control-Set Model Predictive Current Control for IPMSM under Model Parameter Mismatches

Zehao Lyu, Xiang Wu, Jie Gao and Guojun Tan
Additional contact information
Zehao Lyu: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China
Xiang Wu: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China
Jie Gao: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China
Guojun Tan: School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221000, China

Energies, 2021, vol. 14, issue 19, 1-13

Abstract: The control performance of the finite control set model predictive current control (FCS-MPCC) for the interior permanent magnet synchronous machine (IPMSM) depends on the accuracy of the mathematical model. A novel robust model predictive current control method based on error compensation is proposed in order to reduce the parameter sensitivity and improve the current control robustness. In this method, the equivalent parameters are obtained from the known voltage and current information at the past time and the error between the predicted current and the actual current at the present time, which is utilized in the two-step prediction process to compensate the parameter mismatch error. Finally, the optimal voltage vector is selected by the cost function. The proposed method is compared with the traditional model predictive current control method through experiments. The experimental results show the effectiveness of the proposed method.

Keywords: permanent magnet synchronous motor; predictive current control; parameter mismatch (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 references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/19/6342/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/19/6342/ (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:19:p:6342-:d:649854

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 ().