Virtual Voltage Vector-Based Model Predictive Current Control for Five-Phase Induction Motor

• Published in: Processes Vol. 10; no. 10; p. 1925
• Main Authors: Zhang, Qingfei, Zhao, Jinghong, Yan, Sinian, Xiong, Yiyong, Ma, Yuanzheng, Chen, Hansi
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2022
• Subjects: Control systems; Electric potential; Electric vehicles; Energy; Equipment and supplies; Fault tolerance; Induction electric motors; Induction motors; Methods; Motor task performance; Multiphase; Performance prediction; Predictive control; Switching; Variables; Voltage; Waveforms; China
• ISSN: 2227-9717; 2227-9717
• DOI: 10.3390/pr10101925

The high-performance control technology of multi-phase motors is a key technology for the application of multi-phase motors in many fields, such as electric transportation. The model predictive current control (MPCC) strategy has been extended to multi-phase systems due to its high dynamic performance. Model-predictive current control faces the problem that it cannot effectively regulate harmonic plane currents, and thus cannot obtain high-quality current waveforms because only one switching state is applied in a sampling period. To solve this problem, this paper uses the virtual vector-based MPCC to select the optimal virtual vector and apply it under the premise that the average value of the harmonic plane voltage in a single switching cycle is zero. Taking a five-phase induction motor as an example, the steady-state and dynamic performance of the proposed virtual vector MPCC and the traditional model predictive current control were simulated, respectively. Simulation results demonstrated the effectiveness of the proposed method in improving waveform quality while maintaining excellent dynamic performance.