Journal of Power Electronics

  • 제20권1호
  • /
  • Pages.176-187
  • /
  • 2020
  • /
  • 1598-2092(pISSN)
  • /
  • 2093-4718(eISSN)
전력전자학회 (The Korean Institute of Power Electronics)
권호 표지
DOI QR코드

DOI QR Code

Multi-step model predictive current control of permanent-magnet synchronous motor

  • Xu, Yanping (Department of Electrical Engineering, Xi'an University of Technology) ;
  • Sun, Yifei (Department of Electrical Engineering, Xi'an University of Technology) ;
  • Hou, Yongle (Department of Electrical Engineering, Xi'an University of Technology)
  • 투고 : 2019.01.11
  • 심사 : 2019.08.19
  • 발행 : 2020.01.20
⟨ 이전 논문 다음 논문 ⟩

초록

The traditional model predictive current control (MPCC) strategy has the advantages of a fast dynamic response and flexible constraint conditions. However, this strategy only determines the optimal voltage vector in a period rather than in multiple periods, which may result in a large current ripple. To solve the above problem, this paper proposes a multi-step MPCC strategy of permanent-magnet synchronous motor. In the proposed multi-step MPCC strategy, the optimal voltage vector and the sub-optimal voltage vector are considered simultaneously. The current response in the next period is predicted on the basis of the optimal and the sub-optimal voltage vectors, respectively. To ensure the optimality of the selected voltage vector in two control periods, the current responses of the two control periods are contrasted. Compared with the traditional MPCC strategy, simulation and experimental results show that the proposed multi-step MPCC strategy can effectively reduce the current ripple and improve the steady-state performance without increasing the switching frequency.

키워드

참고문헌

  1. Petrov, I., Niemela, M., Ponomarev, P., Pyrhonen, J.: Rotor surface ferrite permanent magnets in electrical machines: advantages and limitations. IEEE Trans. Ind. Electron. 64(7), 5314-5322 (2017) https://doi.org/10.1109/TIE.2017.2677320
  2. Wang, W., Zhang, J., Cheng, M.: Common model predictive control for permanent-magnet synchronous machine drives considering single-phase open-circuit fault. IEEE Trans. Power Electron. 32(7), 5862-5872 (2017) https://doi.org/10.1109/TPEL.2016.2621745
  3. Kim, S., Park, S., Kwak, S.: Simplified model predictive control method for three-phase four-leg voltage source inverters. J. Power Electron. 16(6), 2231-2242 (2016) https://doi.org/10.6113/JPE.2016.16.6.2231
  4. Vafaie, M.H., Dehkordi, B.M.: Approach for classifying direct PCs applied to AC motor drives. IET Electric Power Appl. 13(3), 385-401 (2019) https://doi.org/10.1049/iet-epa.2018.5291
  5. Vazquez, S., Rodriguez, J., Rivera, M., Franquelo, L.G., Norambuena, M.: Model predictive control for power converters and drives: advances and trends. IEEE Trans. Ind. Electron. 64(2), 935-947 (2017) https://doi.org/10.1109/TIE.2016.2625238
  6. Karamanakos, P., Geyer, T., Aguilera, R.P.: Long-horizon direct model predictive control: modified sphere decoding for transient operation. IEEE Trans. Ind. Appl. 54(6), 6060-6070 (2018) https://doi.org/10.1109/tia.2018.2850336
  7. Zhang, Y., Xu, D., Huang, L.: Generalized multiple-vector-based model predictive control for PMSM drives. IEEE Trans. Ind. Electron 65(12), 9356-9366 (2018) https://doi.org/10.1109/tie.2018.2813994
  8. Aguilera, R.P., Lezana, P., Quevedo, D.E.: Finite-control-set model predictive control with improved steady-state performance. IEEE Trans. Ind. Inform 9(2), 658-667 (2013) https://doi.org/10.1109/TII.2012.2211027
  9. Jin, T., Shen, X., Su, T., Flesch, R.: Model predictive voltage control based on finite control set with computation time delay compensation for PV systems. IEEE Trans. Energy Convers. 34(1), 330-338 (2019) https://doi.org/10.1109/tec.2018.2876619
  10. Zhang, Y.C., Yang, H.T.: Two-vector-based model predictive torque control without weighting factors for induction motor drives. IEEE Trans. Power Electron. 31(2), 1381-1390 (2016) https://doi.org/10.1109/TPEL.2015.2416207
  11. Wang, X.H., Sun, D.: Three-vector-based low-complexity model predictive direct power control strategy for doubly fed induction generators. IEEE Trans. Power Electron. 32(1), 773-782 (2017) https://doi.org/10.1109/TPEL.2016.2532387
  12. Siami, M., Khaburi, D.A.: Torque ripple reduction of predictive torque control for PMSM drives with parameter mismatch. IEEE Trans. Ind. Electron. 32(9), 7160-7168 (2017) https://doi.org/10.1109/TPEL.2016.2630274
  13. Siami, M., Khaburi, D.A.: Robustness improvement of predictive current control using Prediction error correction for permanent-magnet synchronous machines. IEEE Trans. Ind. Electron. 63(6), 3458-3466 (2016) https://doi.org/10.1109/TIE.2016.2521734
  14. Cortes, P., Rodriguez, J.: Delay compensation in model predictive current control of a three-phase inverter. IEEE Trans. Ind. Electron. 59(2), 1323-1325 (2012) https://doi.org/10.1109/TIE.2011.2157284
  15. Song, W., Le, S., Wu, X., Ruan, Y.: An improved model predictive direct torque control for induction machine drives. J. Power Electronics 17(3), 674-685 (2017) https://doi.org/10.6113/JPE.2017.17.3.674
  16. Baidya, R., Aguilera, R.P.: Multistep model predictive control for cascaded H-bridge inverters formulation and analysis. IEEE Trans. Power Electron. 33(1), 876-886 (2018) https://doi.org/10.1109/TPEL.2017.2670567
  17. Karamanakos, P., Geyer, T., Manias, S.: Direct voltage control of DC-DC boost converters using enumeration-based model predictive control. IEEE Trans. Power Electron. 29(2), 968-978 (2014) https://doi.org/10.1109/TPEL.2013.2256370
  18. Ayad, A., Karamanakos, P.: Direct model predictive current control strategy of quasi-Z-source inverters. IEEE Trans. Power Electron. 32(7), 5786-5801 (2017) https://doi.org/10.1109/TPEL.2016.2610459
  19. Geyer, T., Quevedo, D.E.: Performance of multistep finite control set model predictive control for power electronics. IEEE Trans. Power Electron. 30(3), 1633-1644 (2015) https://doi.org/10.1109/TPEL.2014.2316173
  20. Zou, J., Xu, W., Yu, X., Liu, Y., Ye, C.: Multistep model predictive control with current and voltage constraints for linear induction machine based urban transportation. IEEE Trans. Veh. Tech. 66(12), 10817-10829 (2017) https://doi.org/10.1109/TVT.2017.2736533
  21. Karamanakos, P., Geyer, T., Oikonomou, N., Kieferndorf, F.D., Manias, S.: Direct model predictive control: a review of strategies that achieve long prediction intervals for power electronics. IEEE Ind. Electron. Mag. 8(1), 32-43 (2014) https://doi.org/10.1109/MIE.2013.2290474
  22. Zhang, X., Zhang, L., Zhang, Y.: Model predictive current control for PMSM drives with parameter robustness improvement. IEEE Trans. Power Electron. 34(2), 1645-1657 (2019) https://doi.org/10.1109/tpel.2018.2835835
  23. Xia, C., Zhou, Z., Wang, Z., Yan, Y., Shi, T.: Computationally efficient multi-step direct predictive torque control for surface-mounted permanent magnet synchronous motor. IET Electric Power Appl. 11(5), 805-814 (2017) https://doi.org/10.1049/iet-epa.2016.0221
  24. Vafaie, M.H., Mirzaeian Dehkordi, B., Moallem, P., Kiyoumarsi, A.: A new predictive direct torque control method for improving both steady-state and transient-state operations of the PMSM. IEEE Trans. Power Electron. 31(5), 3738-3753 (2016) https://doi.org/10.1109/TPEL.2015.2462116

피인용 문헌

  1. Research on Grey Predictive Control of PMSM Based on Reduced-order Luenberger Observer vol.16, pp.5, 2020, https://doi.org/10.1007/s42835-021-00797-3