volume | PIER Journals

Abstract

Outer rotor coreless bearingless permanent magnet synchronous generator is a complex and strongly coupled nonlinear system. The stable suspension and voltage of generator are always the focus and difficulty of research. The fuzzy dynamic sequential model predictive torque control method based on prediction error compensation is proposed. Firstly, the basic structure and working principle of the outer rotor coreless bearingless permanent magnet synchronous generator are introduced in this paper, and the mathematical model of voltage and suspension force is established. Secondly, the mathematical model is carried out to obtain the prediction equation, and the prediction error compensation is carried out to the prediction equation, and then the number of the first output voltage vectorsis determined by fuzzy controller. Finally, the designed control system is simulated and experimentally studied. The simulated and experimental results show that this control method can obtain good voltage and suspension response, and the outer rotor coreless bearingless permanent magnet synchronous generator has good dynamic performance and stability.

1. Ooshima, Masahide, Akira Chiba, Tadashi Fukao, and M. Azizur Rahman, "Design and analysis of permanent magnet-type bearingless motors," IEEE Transactions on Industrial Electronics, Vol. 43, No. 2, 292-299, 1996.

2. Asama, Junichi, Akihito Mouri, Takaaki Oiwa, and Akira Chiba, "Suspension force investigation for consequent-pole and surface-mounted permanent magnet bearingless motors with concentrated winding," 2015 IEEE International Electric Machines & Drives Conference (IEMDC), 780-785, Coeur d'Alene, ID, USA, 2015.

3. Diao, Xiaoyan, Huangqiu Zhu, Yuemei Qin, and Yizhou Hua, "Torque ripple minimization for bearingless synchronous reluctance motor," IEEE Transactions on Applied Superconductivity, Vol. 28, No. 3, 1-5, Apr. 2018.

4. Ooshima, Masahide, Syuu Kitazawa, Akira Chiba, Tadashi Fukao, and D. G. Dorrell, "Design and analyses of a coreless-stator-type bearingless motor/generator for clean energy generation and storage systems," IEEE Transactions on Magnetics, Vol. 42, No. 10, 3461-3463, Oct. 2006.

5. Tomlinson, Males, Hendrik du Toit Mouton, Ralph Kennel, and Peter Stolze, "A fixed switching frequency scheme for finite-control-set model predictive control --- Concept and algorithm," IEEE Transactions on Industrial Electronics, Vol. 63, No. 12, 7662-7670, 2016.

6. Cortes, Patricio, Samir Kouro, Bruno La Rocca, Rene Vargas, Jose Rodriguez, Jose I. Leon, Sergio Vazquez, and Leopoldo G. Franquelo, "Guidelines for weighting factors design in model predictive control of power converters and drives," 2009 IEEE International Conference on Industrial Technology, 1-7, 2009.

7. Muddineni, Vishnu Prasad, Anil Kumar Bonala, and Srinivasa Rao Sandepudi, "Enhanced weighting factor selection for predictive torque control of induction motor drive based on VIKOR method," IET Electric Power Applications, Vol. 10, No. 9, 877-888, 2016.

8. Muddineni, Vishnu Prasad, Srinivasa Rao Sandepudi, and Anil Kumar Bonala, "Finite control set predictive torque control for induction motor drive with simplified weighting factor selection using TOPSIS method," IET Electric Power Applications, Vol. 11, No. 5, 749-760, 2017.

9. 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, Mar. 2012.

10. Justo, Jackson John, Francis Mwasilu, Eun-Kyung Kim, Jinuk Kim, Han Ho Choi, and Jin-Woo Jung, "Fuzzy model predictive direct torque control of IPMSMs for electric vehicle applications," IEEE/ASME Transactions on Mechatronics, Vol. 22, No. 4, 1542-1553, Aug. 2017.

11. Dragičević, Tomislav and Mateja Novak, "Weighting factor design in model predictive control of power electronic converters: An artificial neural network approach," IEEE Transactions on Industrial Electronics, Vol. 66, No. 11, 8870-8880, Nov. 2019.

12. Rojas, Christian A., Jose Rodriguez, Felipe Villarroel, José R. Espinoza, César A. Silva, and Mauricio Trincado, "Predictive torque and flux control without weighting factors," IEEE Transactions on Industrial Electronics, Vol. 60, No. 2, 681-690, Feb. 2013.

13. Ravi Eswar, Kodumur Meesala, Kunisetti V. Praveen Kumar, and Thippiripati Vinay Kumar, "Modified predictive torque and flux control for open end winding induction motor drive based on ranking method," IET Electric Power Applications, Vol. 12, No. 4, 463-473, 2018.

14. Norambuena, Margarita, Jose Rodriguez, Zhenbin Zhang, Fengxiang Wang, Cristian Garcia, and Ralph Kennel, "A very simple strategy for high-quality performance of AC machines using model predictive control," IEEE Transactions on Power Electronics, Vol. 34, No. 1, 794-800, Jan. 2019.

15. Zhang, Yongchang, Boyue Zhang, Haitao Yang, Margarita Norambuena, and Jose Rodriguez, "Generalized sequential model predictive control of IM drives with field-weakening ability," IEEE Transactions on Power Electronics, Vol. 34, No. 9, 8944-8955, Sep. 2019.

16. Li, Yucai and Huangqiu Zhu, "Three-vector model predictive suspension force control for bearingless permanent magnet slice motor," IEEE Transactions on Power Electronics, Vol. 38, No. 7, 8282-8290, Jul. 2023.

Mr. Shuai Zhuang

Dr. Gai Liu

Prof. Huangqiu Zhu