volume | PIER Journals

Abstract

Aiming at the problem of large torque ripple caused by large tracking error between actual torque and reference torque in commutation region in direct instantaneous torque control (DITC) algorithm of switched reluctance motor (SRM) based on torque sharing function (TSF), a torque compensation method combining TSF-DITC and model predictive control (MPC) is proposed. Sectors are subdivided in the commutation region according to the rotor position. Different voltage states are selected in different sectors to fully compensate for the tracking error between the actual phase torque and the reference torque distributed by TSF, and then the total torque ripple is greatly reduced. At the same time, the algorithm also effectively reduces the candidate voltage states at the current time and reduces the computational burden. The simulation comparison with TSF-DITC shows that the algorithm (TSF-PDITC) has better steady-state and dynamic performance.

1. Bilgin, B., B. Howey, A. D. Callegaro, et al. "Making the case for switched reluctance motors for propulsion applications," IEEE Transactions on Vehicular Technology, Vol. 69, No. 7, 7172-7186, 2020.
doi:10.1109/TVT.2020.2993725 Google Scholar

2. Zan, X., Z. Jiang, K. Ni, et al. "Modular battery management for SRM drives in hybrid vehicles based on a novel modular converter," IEEE Access, Vol. 8, No. 1, 136296-136306, 2020.
doi:10.1109/ACCESS.2020.3011451 Google Scholar

3. Aiso, K. and A. Kan, "High speed SRM using vector control for electric vehicle," Transactions on Electrical Machines and Systems, Vol. 4, No. 1, 61-68, 2020.
doi:10.30941/CESTEMS.2020.00009 Google Scholar

4. Sun, Q., J. Wu, C. Gan, et al. "Multi-level converter-based torque sharing function control strategy for switched reluctance motors," International Conference on Electrical Machines Systems, 1-5, IEEE, 2017. Google Scholar

5. Liu, Y., L. I. Jie, and C. Shan, "Direct instantaneous torque control of switched reluctance motor based on optimal angle adaptive TSF," Journal of Beijing University of Aeronautics and Astronautics, Vol. 45, No. 11, 2152-2159, 2019. Google Scholar

6. Li, Z. and Z. Kan, "A high efficiency direct instantaneous torque control of SRM," Transactions of China Electro technical Society, Vol. 25, No. 8, 31-37, 2010. Google Scholar

7. Valenciagarcia, D. F., R. Tarvirdilu-Asl, C. Garcia, et al. "A review of predictive control techniques for switched reluctance machine drives," IEEE Transactions on Energy Conversion, Vol. 36, No. 2, 1323-1335, 2020.
doi:10.1109/TEC.2020.3047981 Google Scholar

8. Valenciagarcia, D. F., R. Tarvirdilu-Asl, C. Garcia, et al. "A review of predictive control techniques for switched reluctance machine drives. Part II: Torque control, assessment and challenges," IEEE Transactions on Energy Conversion, Vol. 36, No. 2, 1323-1335, 2020.
doi:10.1109/TEC.2020.3047981 Google Scholar

9. Elmorshedy, M. F., W. Xu, F. El-Sousy, et al. "Recent achievements in model predictive control techniques for industrial motor: A comprehensive state-of-the-art," IEEE Access, Vol. 9, No. 1, 58170-58191, 2021.
doi:10.1109/ACCESS.2021.3073020 Google Scholar

10. Shang, C., A. Xu, L. Huang, et al. "Flux linkage optimization for direct torque control of switched reluctance motor based on model predictive control," IEEE Transactions on Electrical and Electronic Engineering, Vol. 14, No. 7, 1105-1113, 2019.
doi:10.1002/tee.22906 Google Scholar

11. Hu, K., L. Guo, and J. Ye, "Model predictive current control of mutually coupled switched reluctance machines using a three-phase voltage source converter," IEEE Applied Power Electronics Conference and Exposition (APEC), 704-710, New Orleans, 2020.
doi:10.1109/APEC39645.2020.9124115 Google Scholar

12. Le-Huy, H. and P. Brunelle, "A versatile nonlinear switched reluctance motor model in Simulink using realistic and analytical magnetization characteristics," Industrial Electronics Society, 6, 2005. Google Scholar

Dr. Yang Yang

Professor Aide Xu

Dr. Bing Leng

Dr. Jinghao Sun

Dr. Kuo Li