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Model Predictive Duty Cycle Control for Three-Phase Vienna Rectifiers With Reduced Neutral-Point Voltage Ripple Under Unbalanced DC Links
Under unbalanced dc links, the control of a three-phase Vienna rectifier is challenging. To deal with the unbalanced dc links, the optimal switching sequence model predictive control (MPC) regulates the neutral-point (NP) voltage through preselecting a redundant vector and grid current by reconstruc...
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Published in: | IEEE journal of emerging and selected topics in power electronics 2022-10, Vol.10 (5), p.5578-5590 |
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Main Authors: | , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Under unbalanced dc links, the control of a three-phase Vienna rectifier is challenging. To deal with the unbalanced dc links, the optimal switching sequence model predictive control (MPC) regulates the neutral-point (NP) voltage through preselecting a redundant vector and grid current by reconstructing duty cycles of the optimal switching sequence. However, its one-redundant-vector-per-control-interval characteristic leads to large NP voltage ripple. To solve this problem, in this article, a model predictive duty cycle control method is proposed for three-phase Vienna rectifiers under unbalanced dc links. First, we study the impacts of duty cycles on the variations of instantaneous current, and then, the three-phase duty cycles are derived by predefined objective function minimization. Second, considering both the operational characteristics and unbalanced dc links of the Vienna rectifier, a new modification method for duty cycles is presented. This method ensures the grid current quality and decouples the control of grid current and NP voltage. Finally, an MPC-based NP voltage control strategy is proposed to reduce the NP voltage ripple. Experimental results demonstrate that the presented method can effectively reduce the NP voltage ripple. |
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ISSN: | 2168-6777 2168-6785 |
DOI: | 10.1109/JESTPE.2022.3175583 |