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2023-06-04
Predictive Current Control of Permanent Magnet Synchronous Motor Based on Parameter Identification
By
Progress In Electromagnetics Research C, Vol. 133, 181-194, 2023
Abstract
Aiming at the unsatisfactory accuracy and speed of traditional parameter identification methods for permanent magnet synchronous motors (PMSM), a parameter identification method based on an improved hunter prey optimization (HPO) algorithm (Tent chaotic initialization and firefly algorithm HPO (TF-HPO)) was proposed. Using the Tent chaotic map, the initial individuals are evenly distributed to enrich their diversity, and the population position is updated using the firefly perturbation algorithm. Simulation and practical experiments show that compared with unmodified algorithm, the improved algorithm has faster convergence speed and higher recognition accuracy, and can effectively identify the parameters of the motor. On this basis, deadbeat predictive current control is implemented, effectively eliminating current static errors and improving the accuracy and stability of the current control system, and can effectively suppress motor torque ripple and current harmonics caused by parameter deviations.
Citation
Chengmin Wang, and Aiyuan Wang, "Predictive Current Control of Permanent Magnet Synchronous Motor Based on Parameter Identification," Progress In Electromagnetics Research C, Vol. 133, 181-194, 2023.
doi:10.2528/PIERC23032903
References

1. Wang, B., X. Chen, Y. Yu, et al. "Robust predictive current control with online disturbance estimation for induction machine drives," IEEE Transactions on Power Electronics, Vol. 32, No. 6, 4663-4674, 2016.
doi:10.1109/TPEL.2016.2602853

2. Wang, Y., X. Wang, W. Xie, et al. "Deadbeat model-predictive torque control with discrete space-vector modulation for PMSM drives," IEEE Transactions on Industrial Electronics, Vol. 64, No. 5, 3537-3547, 2017.
doi:10.1109/TIE.2017.2652338

3. Wang, B., X. Zhang, and H. B. Gooi, "An SI-MISO boost converter with deadbeat-based control for electric vehicle applications," IEEE Transactions on Vehicular Technology, Vol. 67, No. 10, 9223-9232, 2018.
doi:10.1109/TVT.2018.2853738

4. Wang, B., U. Manandhar, X. Zhang, et al. "Deadbeat control for hybrid energy storage systems in DC microgrids," IEEE Transactions on Sustainable Energy, Vol. 10, No. 4, 1867-1877, 2018.
doi:10.1109/TSTE.2018.2873801

5. Wang, P., Y. Bi, F. Gao, et al. "An improved deadbeat control method for single-phase PWM rectifiers in charging system for EVs," IEEE Transactions on Vehicular Technology, Vol. 68, No. 10, 9672-9681, 2019.
doi:10.1109/TVT.2019.2937653

6. Saeed, M. S. R., W. Song, B. Yu, et al. "Low-complexity deadbeat model predictive current control with duty ratio for five-phase PMSM drives," IEEE Transactions on Power Electronics, Vol. 35, No. 11, 12085-12099, 2020.
doi:10.1109/TPEL.2020.2983048

7. Cao, Y., R. Mao, L. Feng, et al. "Multiparameter identification of permanent magnet synchronous motors based on improved sparrow search algorithm," New Technology of Electrical Energy, Vol. 41, No. 05, 26-34, 2022.

8. Li, Y., X. Dong, H. Wei, et al. "Parameter identification of permanent magnet synchronous motors based on improved model reference adaptive systems," Control Theory and Application, Vol. 37, No. 09, 1983-1988, 2020.

9. Li, W. and Z. Du, "Parameter identification of permanent magnet synchronous motor based on improved grey wolf optimization algorithm," Modular Machine Tool and Automatic Machining Technology, Vol. 557, No. 07, 113-117, 2020.

10. Wu, Z., D. Yu, and X. Kang, "Parameter identification of solar cell models based on improved ant lion optimization algorithm," Acta Energiae Solaris Sinica, Vol. 40, No. 12, 3435-3443, 2019.

11. Liu, X., W. Hu, Y. Zou, et al. "Multi parameter identification of permanent magnet synchronous motors using improved particle swarm optimization," Journal of Electrical Machinery and Control, Vol. 24, No. 07, 112-120, 2020.

12. Turker, T., U. Buyukkeles, and A. F. Bakan, "A robust predictive current controller for PMSM drives," IEEE Transactions on Industrial Electronics, Vol. 63, No. 6, 3906-3914, 2016.
doi:10.1109/TIE.2016.2521338

13. Wang, Z., A. Yu, X. Li, G. Zhang, and C. Xia, "A novel current predictive control based on fuzzy algorithm for PMSM," IEEE Journal of Emerging and Selected Topics in Power Electronics, 990-1001, 2019.
doi:10.1109/JESTPE.2019.2902634

14. Siami, M., D. A. Khaburi, M. Rivera, and J. Rodriguez, "An experimental evaluation of predictive current control and predictive torque control for a PMSM fed by a matrix converter," IEEE Transactions on Industrial Electronics, Vol. 64, No. 11, 8459-8471, 2018.
doi:10.1109/TIE.2017.2703658

15. El-Sousy, F. F. M., "Hybrid-based wavelet-neural-network tracking control for permanent-magnet synchronous motor servo drives," IEEE Transactions on Industrial Electronics, Vol. 57, No. 9, 3157-3166, 2010.
doi:10.1109/TIE.2009.2038331

16. Wang, Y., X. Wang, W. Xie, et al. "Deadbeat model-predictive torque control with discrete space-vector modulation for PMSM drives," IEEE Transactions on Industrial Electronics, Vol. 64, No. 5, 3537-3547, 2017.
doi:10.1109/TIE.2017.2652338

17. Wu, C., Y. Zhao, and M. Sun, "Multi-parameter online identification of permanent magnet synchronous motors using measured voltages," Proceedings of the CSEE, Vol. 40, No. 13, 4329-4340, 2020.

18. Wang, G., Current predictive control and current static error elimination algorithm for permanent magnet AC servo systems, Harbin Institute of Technology, 2014.

19. Naruei, I., F. Keynia, and A. Sabbagh Molahosseini, "Hunter-prey optimization: Algorithm and applications," Soft Computing, Vol. 26, 1279-1314, 2022.
doi:10.1007/s00500-021-06401-0

20. Xue, J., Research and application of a new swarm intelligence optimization technology, Donghua University, 2020.