Finite Control Set Model Predictive Current Control with Constant Switching Frequency Regulation for <scp>PMSM</scp> Drives

Due to the absence of a modulator stage, finite control set model predictive control (FCS‐MPC) exhibits a variable switching frequency, which is one of the main drawbacks when it is applied to power converters and motor drives. Conventional methods achieve the constant switching frequency by modifying the cost function. However, an additional weighting factor is required. In this paper, a novel FCS‐MPC with the constant switching frequency is proposed. To avoid the use of a weighting factor, a current error control band (CECB) is used to balance the current control and switching frequency regulation. Furthermore, it is investigated that the switching frequency decreases as the width of the CECB increases. Based on this principle, a switching frequency controller is proposed to online adjust the width of the CECB according to the switching frequency error between the reference and feedback values. This method allows FCS‐MPC to operate at a reduced switching frequency. More importantly, the switching frequency can be concentrated at a constant value without requiring the weighting factor. The proposed method is verified experimentally under various operating conditions. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Authors

Institutions

Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2025-04-27
DOI
https://doi.org/10.1002/tee.70045
Citations
2
Primary Topic
Multilevel Inverters and Converters
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Finite Control Set Model Predictive Current Control with Constant Switching Frequency Regulation for PMSM Drives

Qingqiang Meng, Liguo Yang, Jingyao Yang, Shilei Li et al.
2 citations
IEEJ Transactions on Electrical and Electronic Engineering
Multilevel Inverters and Converters
1.46
article

Finite Control Set Model Predictive Current Control with Constant Switching Frequency Regulation for PMSM Drives

Qingqiang Meng, Liguo Yang, Jingyao Yang, Shilei Li, Mengyu Zhang, Hongmei Li
article en
2 citations

Abstract

Due to the absence of a modulator stage, finite control set model predictive control (FCS‐MPC) exhibits a variable switching frequency, which is one of the main drawbacks when it is applied to power converters and motor drives. Conventional methods achieve the constant switching frequency by modifying the cost function. However, an additional weighting factor is required. In this paper, a novel FCS‐MPC with the constant switching frequency is proposed. To avoid the use of a weighting factor, a current error control band (CECB) is used to balance the current control and switching frequency regulation. Furthermore, it is investigated that the switching frequency decreases as the width of the CECB increases. Based on this principle, a switching frequency controller is proposed to online adjust the width of the CECB according to the switching frequency error between the reference and feedback values. This method allows FCS‐MPC to operate at a reduced switching frequency. More importantly, the switching frequency can be concentrated at a constant value without requiring the weighting factor. The proposed method is verified experimentally under various operating conditions. © 2025 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic EngineeringVol. 20(10)
Hefei University of Technology (CN)
Openalex Percentile: Top 18%
Multilevel Inverters and Converters
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.