Affiliation:
1. School of Information Engineering, Nanchang University Nanchang Jiangxi 330031 China
Abstract
Compared to the model predictive control (MPC) technique, the modulated MPC (M2PC) method applies multiple voltage vectors in order within one switching cycle, enabling a fixed switching frequency and better motor control performance. However, the M2PC technique suffers from a significant computational burden and imprecise allocation method of the vector action time, affecting the control performance. To address these two issues, this paper proposes an improved M2PC method that utilizes the information of projection of the reference vector on the selected voltage vectors for efficiently selecting the optimal active vectors and also accurately calculating their action time. Compared to the conventional M2PC, the proposed technique demonstrates both excellent dynamic performance with reduced execution time by 15.3% and superior steady‐state performance in terms of lower torque/speed ripple as well as fewer current harmonics. Those benefits have been proven by the results of a 2.5k rpm permanent magnet synchronous motor drive. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.
Funder
Natural Science Foundation of Jiangxi Province
Cited by
2 articles.
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1. Lagrange Multipliers Aided Modulated Model Predictive Control Technique for PMSM Drives;IEEJ Transactions on Electrical and Electronic Engineering;2024-06-28
2. Improved Modulated MPC Technique using the Virtual Vectors by Duty Cycle Reconstruction;2024 IEEE 10th International Power Electronics and Motion Control Conference (IPEMC2024-ECCE Asia);2024-05-17