LAPSE:2023.25836
Published Article
LAPSE:2023.25836
A Dual-Vector Modulated Model Predictive Control Method for Voltage Source Inverters with a New Duty Cycle Calculation Method
Lingzhi Cao, Yanyan Li, Xiaoying Li, Leilei Guo, Nan Jin, Hong Cao
March 31, 2023
Recently, model predictive control (MPC) methods have been widely used to achieve the control of two-level voltage source inverters due to their superiorities. However, only one of the eight basic voltage vectors is applied in every control cycle in the conventional MPC system, resulting in large current ripples and distortions. To address this issue, a dual-vector modulated MPC method is presented, where two voltage vectors are selected and utilized to control the voltage source inverter in every control cycle. The duty cycle of each voltage vector is figured out according to the hypothesis that it is inversely proportional to the square root of its corresponding cost function value, which is the first contribution of this paper. The effectiveness of this assumption is verified for the first time by a detailed theoretical analysis shown in this paper based on the geometrical relationship of the voltage vectors, which is another contribution of this paper. Moreover, further theoretical analysis shows that the proposed dual-vector modulated MPC method can also be extended to control other types of inverters, such as three-phase four-switch inverters. Detailed experimental results validate the effectiveness of the presented strategy.
Keywords
dual-vector, duty cycle, Model Predictive Control, theoretical analysis
Subject
Suggested Citation
Cao L, Li Y, Li X, Guo L, Jin N, Cao H. A Dual-Vector Modulated Model Predictive Control Method for Voltage Source Inverters with a New Duty Cycle Calculation Method. (2023). LAPSE:2023.25836
Author Affiliations
Cao L: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Li Y: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Li X: Senyuan Electric Co., Ltd., Changge 461500, China
Guo L: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China
Jin N: School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, China [ORCID]
Cao H: Senyuan Electric Co., Ltd., Changge 461500, China
Journal Name
Energies
Volume
13
Issue
16
Article Number
E4200
Year
2020
Publication Date
2020-08-14
Published Version
ISSN
1996-1073
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PII: en13164200, Publication Type: Journal Article
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LAPSE:2023.25836
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doi:10.3390/en13164200
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