volume | PIER Journals

Abstract

This paper addresses the susceptibility of motor parameters to external disturbances during the operation of three-vector model predictive current control (TV-MPCC) for permanent magnet-assisted synchronous reluctance motors (PMA-SynRMs), which leads to increased current fluctuations and reduced tracking precision. To enhance the control system's stability, a step-by-step parameter identification approach is proposed. First, the proposed method devises six switching configurations, considers eight potential current prediction points generated by voltage vectors, and reformulates the value function. Next, a model reference adaptive system (MRAS) is employed to incrementally identify the motor's d and q axis inductances, resistance, and flux linkage. These identified parameters are used to update the model in real time. In this study, a 3kW PMA-SynRM serves as the control object for simulation verification. Results indicate that the TV-MPCC based on step-by-step parameter identification has obvious improvement in current tracking static error and peak value of current fluctuation.

1. Jia, Shaofeng, Ping Zhang, Deliang Liang, Maocun Dai, and Jinjun Liu, "Design and comparison of three different types of efficiency machines," 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 1-4, Harbin, China, 2019.

2. Cao, Hengpei, Mengmeng Ai, and Yanbo Wang, "Research status and development trend of permanent magnet assisted synchronous reluctance motor," Transactions of China Electrotechnical Society, Vol. 37, No. 18, 4575-4592, 2022. Google Scholar

3. Zheng, S. Y., X. Y. Zhu, L. Xu, et al., "Design and performance analysis of PM-assisted synchronous reluctance motor considering high torque-quality ratio," Chinese Journal of Electrical Engineering, Vol. 42, No. 19, 7236-7248, 2022. Google Scholar

4. Leuzzi, Riccardo, Paolo Cagnetta, Simone Ferrari, Paolo Pescetto, Gianmario Pellegrino, and Francesco Cupertino, "Transient overload characteristics of PM-assisted synchronous reluctance machines, including sensorless control feasibility," IEEE Transactions on Industry Applications, Vol. 55, No. 3, 2637-2648, 2019. Google Scholar

5. Huang, H. and Y. S. Hu, Design and Application of Permanent Magnet Assisted Synchronous Reluctance Motor, Machinery Industry Press, Beijing, 2017.

6. Chen, Yang, Bai Baodong, Chen Dezhi, et al., "Design and analysis of a variable flux permanent magnet assisted synchronous motor," Transactions of China Electrotechnical Society, Vol. 34, No. 3, 489-496, 2019. Google Scholar

7. Niazi, Peyman, Hamid A. Toliyat, and Abbas Goodarzi, "Robust maximum torque per ampere (MTPA) control of PM-assisted SynRM for traction applications," IEEE Transactions on Vehicular Technology, Vol. 56, No. 4, 1538-1545, 2007. Google Scholar

8. Davari, S. Alireza, Davood Arab Khaburi, and Ralph Kennel, "An improved FCS-MPC algorithm for an induction motor with an imposed optimized weighting factor," IEEE Transactions on Power Electronics, Vol. 27, No. 3, 1540-1551, 2012. Google Scholar

9. Xu, Yanping, Baocheng Zhang, and Qin Zhou, "Two-vector based model predictive current control for permanent magnet synchronous motor," Transactions of China Electrotechnical Society, Vol. 32, No. 20, 222-230, 2017. Google Scholar

10. Wang, C., "Research on current control strategy of permanent magnet synchronous motor with double vector model prediction," Harbin University of Science and Technology, 2022.

11. Xu, Yanping, Jibing Wang, Baocheng Zhang, and Q. Zhou, "Three-vector-based model predictive current control for permanent magnet synchronous motor," Transactions of China Electrotechnical Society, Vol. 33, No. 5, 980-988, 2018. Google Scholar

12. Li, Xinyue and Ralph Kennel, "General formulation of Kalman-filter-based online parameter identification methods for VSI-fed PMSM," IEEE Transactions on Industrial Electronics, Vol. 68, No. 4, 2856-2864, 2021. Google Scholar

13. Gao, F. Y., D. H. Luo, M. M. Li, et al., "Predictive current control of permanent magnet synchronous motor with on-line correction of mismatch parameters," Control Theory & Applications, Vol. 38, No. 05, 603-614, 2021. Google Scholar

14. Li, Y. J., X. Dong, H. F. Wei, et al., "Parameter identification of permanent magnet synchronous motor based on improved model reference adaptive system," Control Theory & Applications, Vol. 37, No. 09, 1983-1988, 2019. Google Scholar

Professor Aide Xu

Mr. Ruijie Liu

Dr. Yubang Yu