Model Predictive Direct Speed Control of Permanent-Magnet Synchronous Motors with Voltage Error Compensation

• Published in: Energies (Basel) Vol. 16; no. 13; p. 5128
• Main Authors: Gao, Lixiao, Chai, Feng
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2023
• Subjects: Algorithms; Compensation; Electric potential; Error compensation; Harmonic distortion; inverter nonlinearity; Inverters; Mathematical models; model predictive control; Neural networks; Nonlinearity; Parameter identification; Permanent magnets; permanent-magnet synchronous motors; Speed control; Synchronous motors; Uncertainty; Voltage; voltage error compensation
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en16135128

Traditional strategies for model predictive direct speed control of permanent-magnet synchronous motors are known to be vulnerable to voltage errors. In this paper, we present a novel approach that compensates for voltage errors arising from inverter nonlinearity and bus voltage uncertainties, while remaining unaffected by parameter errors. Initially, we conducted a detailed analysis to assess the impact of inverter nonlinearity and bus voltage uncertainties. Subsequently, we proposed a voltage error compensation strategy based on bus voltage identification. Using this strategy, the identified voltage error is effectively compensated within candidate voltage vectors. To validate the effectiveness of our proposed method, we conducted comprehensive experiments. The results demonstrate notable improvements compared with traditional model predictive control. Specifically, our method successfully reduces the total harmonic distortion of phase currents from 23.2% and 49.6% to 11.6% and 13.9%, respectively. Additionally, it accurately identifies voltage errors, even in the presence of parameter errors. Overall, our proposed method presents a robust and reliable solution for addressing voltage errors, thereby enhancing the performance and stability of the system.