Non-Weighted Two-Stage Model Predictive Control Strategy Based on Three-Level NPC Inverter

Guifeng Wang, Peiru Li and Yu Wang ()
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Guifeng Wang: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221000, China
Peiru Li: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221000, China
Yu Wang: School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221000, China

Energies, 2024, vol. 17, issue 8, 1-21

Abstract: This paper investigates the asynchronous motors driven by a Three-Level Neutral-Point-Clamped Voltage Source Inverter (3L-NPC-VSI) and aims to achieve control without weight factors and reduce torque ripple. It puts forward a non-weighted two-stage Finite-Control-Set Model Predictive Control (FCS-MPC) strategy. First, a hierarchical optimization method is adopted to address the difficulty of setting weight factors in traditional FCS-MPC applications. The method offers stratified designs of three performance indices, voltage jump, common-mode voltage, and current tracking, obviating the need for weight factor setting and reducing the calculation load of predictions. Secondly, to further mitigate torque ripple, an optimal vector or vector combination is implemented at the current control layer by adhering to the principle of minimal current tracking error. During the selection of the optimal vector combination, the first vector of the combination is chosen to be the vector at the end of the present cycle. This ensures that there is at most one switch within each control period, reducing the switching losses of the two-stage FCS-MPC. Lastly, detailed simulation and experimental analyses are conducted to verify the feasibility and effectiveness of the proposed strategy.

Keywords: FCS-MPC; weightless factor; two stage; 3L-NPC-VSI; torque ripple (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: 2024
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