doi: 10.17586/2226-1494-2023-23-2-390-402


Comparative analysis of switched reluctance motor control algorithms

G. L. Demidova, Y. D. Derbikov, F. S. Petrikov, D. V. Lukichev, R. Strzelecki, A. S. Anuchin


Read the full article  ';
Article in English

For citation:
Demidova G.L., Derbikov Y.D., Petrikov F.S., Lukichev D.V., Strzelecki R., Anuchin A.S. Comparative analysis of switched reluctance motor control algorithms. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2023, vol. 23, no. 2, pp. 390–402 (in Russian). doi: 10.17586/2226-1494-2023-23-2-390-402


Abstract
Nowadays it has become possible to develop inexpensive modern control systems for nonlinear complexity electromechanical objects due to the development of microprocessor technology and power electronics. Switched reluctance electric machines are among these devices. It makes it possible to widely use such electric machines in various practical implementations, in particular, in traction drives, electric drives of oil and gas drilling rigs, and in other applications. The switched reluctance electric machine is a non-linear object, and its control methods require formalization and grouping. The manuscript considers the design and functional features of switched reluctance electrical machines. The main methods of controlling these electrical machine types are given. Comparative analysis of the most known methods is carried out. The main classical methods of switched reluctance electric machine control are considered, such as a relay current controller with a limitation, the method of controlling the turn on/off angles and controlling the DC link voltage. Transient responses in the electric drive system are demonstrated using the considered methods. It is shown that by adjusting the on/off angles, it is possible to reduce the torque oscillation coefficient. The identified features of the presented methods will make it possible to simplify and reduce the development time for an effective control system for switched reluctance electrical machines as well as to reduce the torque ripple.

Keywords: switched reluctance motor, control system, turn on angle, speed control, simulation modeling

References
  1. Abdalmagid M., Sayed E., Bakr M.H., Emadi A. Geometry and topology optimization of switched reluctance machines: A review. IEEE Access, 2022, vol. 10, pp. 5141–5170. https://doi.org/10.1109/ACCESS.2022.3140440
  2. Prasad N., Jain S., Gupta S. Review of linear switched reluctance motor designs for linear propulsion applications. CES Transactions on Electrical Machines and Systems, 2022, vol. 6, no. 2, pp. 179–187. https://doi.org/10.30941/CESTEMS.2022.00024
  3. Mohanraj D., Gopalakrishnan J., Chokkalingam B., Mihet-Popa L. Critical aspects of electric motor drive controllers and mitigation of torque ripple—review. IEEE Access, 2022, vol. 10, pp. 73635–73674. https://doi.org/10.1109/ACCESS.2022.3187515
  4. Xia Z., Bilgin B., Nalakath S., Emadi A. A new torque sharing function method for switched reluctance machines with lower current tracking error. IEEE Transactions on Industrial Electronics, 2021, vol. 68, no. 11, pp. 10612–10622. https://doi.org/10.1109/TIE.2020.3037987
  5. Deng X., Mecrow B. A direct energy control technique for torque ripple and DC-link voltage ripple reduction in switched reluctance drive systems. Proc. of the 2020 International Conference on Electrical Machines (ICEM), 2020, pp. 2035–2040. https://doi.org/10.1109/ICEM49940.2020.9270705
  6. Nandu Krishnan A.M., Monish M., Vivek R.S. Direct torque control based on inductance profile for four phase switched reluctance motor. Proc. of the 2020 International Conference on Power Electronics and Renewable Energy Applications (PEREA), 2020, pp. 1–5. https://doi.org/10.1109/PEREA51218.2020.9339789
  7. Li Y., Tang Y., Chang J., Li A. Continuous sliding mode control and simulation of SRM. Proc. of the IEEE 10th International Conference on Cognitive Informatics and Cognitive Computing (ICCI-CC'11), 2011, pp. 314–317. https://doi.org/10.1109/COGINF.2011.6016158
  8. Sun X., Wu J., Lei G., Guo Y., Zhu J. Torque ripple reduction of SRM drive using improved direct torque control with sliding mode controller and observer. IEEE Transactions on Industrial Electronics, 2021, vol. 68, no. 10, pp. 9334–9345. https://doi.org/10.1109/TIE.2020.3020026
  9. Cheng Y., Li P. Research on switched reluctance motor speed control system with variable universe fuzzy PID. Proc. of the 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), 2020, pp. 2285–2289. https://doi.org/10.1109/ITNEC48623.2020.9084650
  10. Sahoo N.C., Panda S.K., Dash P.K. A current modulation scheme for direct torque control of switched reluctance motor using fuzzy logic. Mechatronics, 2000, vol. 10, no. 3, pp. 353–370. https://doi.org/10.1016/S0957-4158(99)00039-2
  11. Rahman K.M., Gopalakrishnan S., Fahimi B., Velayutham Rajarathnam A., Ehsani M. Optimized torque control of switched reluctance motor at all operational regimes using neural network. IEEE Transactions on Industry Applications, 2001, vol. 37, no. 3, pp. 904–913. https://doi.org/10.1109/28.924774
  12. Han L., Xu A., Zhu J., Zhang W. Torque observer of SRM based on BP neural network optimized by bat algorithm. Proc. of the 2019 22nd International Conference on Electrical Machines and Systems (ICEMS), 2019, pp. 1–6. https://doi.org/10.1109/ICEMS.2019.8921967
  13. Fang G., Ye J., Xiao D., Xia Z., Emadi A. Low-ripple continuous control set model predictive torque control for switched reluctance machines based on equivalent linear SRM model. IEEE Transactions on Industrial Electronics, 2022, vol. 69, no. 12, pp. 12480–12495. https://doi.org/10.1109/TIE.2021.3130344
  14. Rodriguez J., Garcia C., Mora A., Flores-Bahamonde F., Acuna P., Novak M., Zhang Y., Tarisciotti L., Davari S.A., Zhang Z., Wang F., Norambuena M., Dragicevic T., Blaabjerg F., Geyer T., Kennel R., Khaburi D.A., Abdelrahem M., Zhang Z., Mijatovic N., Aguilera R.P. Latest Advances of model predictive control in electrical drives–Part I: Basic concepts and advanced strategies. IEEE Transactions on Power Electronics, 2022, vol. 37, no. 4, pp. 3927–3942. https://doi.org/10.1109/TPEL.2021.3121532
  15. Anuchin A., Demidova G.L., Hao C., Zharkov A., Bogdanov A., Šmídl V. Continuous control set model predictive control of a switch reluctance drive using lookup tables. Energies, 2020, vol. 13, no. 13, pp. 3317. https://doi.org/10.3390/en13133317
  16. Cheshmehbeigi H.M., Karami E. Maximum output torque control in improved flux path homopolar brushless DC motor with axillary field by using optimal control of turn-on and turn-off angles in variable speed applications. IEEE Journal of Emerging and Selected Topics in Power Electronics, 2018, vol. 6, no. 4, pp. 1722–1731. https://doi.org/10.1109/JESTPE.2018.2850349
  17. Shin S., Kawagoe N., Kosaka T., Matsui N. Study on commutation control method for reducing noise and vibration in SRM. IEEE Transactions on Industry Applications, 2018, vol. 54, no. 5, pp. 4415–4424. https://doi.org/10.1109/TIA.2018.2831173
  18. Shevkunova A.V. Improving the design of the active part of the switched reluctance machine. Dissertation for the degree of candidate of technical sciences. Rostov-on-Don, 2018, 150 p. (in Russian)
  19. Aliamkin D.I. Development and research of a two-phase switched reluctance electric motor drive for hot water pumps. Dissertation for the degree of candidate of technical sciences. Moscow, 2012, 229 p. (in Russian)
  20. Bychkov M.G. Fundamentals of the theory, control and design of a switched reluctance electric motor drive. Thesis for the degree of Doctor of Technical Sciences, Moscow, 1999, 382 p. (in Russian)
  21. Krasovskii A.B. Simulation models in the theory and practice of switched reluctance electric motor drive. Thesis for the degree of Doctor of Technical Sciences, Moscow, 2003, 321 p. (in Russian)
  22. Qiao D., Huang C., Cai M. The design of fluxlinkage measurement for switched reluctance motor.Journal of Physics: Conference Series, 2019, vol. 1176, pp. 052036. https://doi.org/10.1088/1742-6596/1176/5/052036
  23. Barnes M., Pollock C. Power electronic converters for switched reluctance drives. IEEE Transactions on Power Electronics, 1998, vol. 13, no. 6, pp. 1100–1111. https://doi.org/10.1109/63.728337
  24. Mahmoud S.M., El-Sherif M.Z., Abdel-Aliem E.S. Studying different types of power converters fed switched reluctance motor. International Journal of Electronics and Electrical Engineering, 2013, vol. 1, no. 4, pp. 281–290. https://doi.org/10.12720/ijeee.1.4.281-290
  25. Pillay P., Cai W. An investigation into vibration in switched reluctance motors. Conference Record of 1998 IEEE Industry Applications Conference. Thirty-Third IAS Annual Meeting (Cat. No.98CH36242), 1998, pp. 341–350 https://doi.org/10.1109/ias.1998.732316
  26. Pupadubsin R., Mecrow B.C., Widmer J.D., Steven A. Smooth voltage PWM for vibration and acoustic noise reduction in switched reluctance machines. IEEE Transactions on Energy Conversion, 2021, vol. 36, no. 3, pp. 1578–1588. https://doi.org/10.1109/TEC.2020.3044917
  27. KrasovskiiA.B. Electrical Technology Russia, 2003, no. 3, pp. 35–45. (in Russian)
  28. Krasovskiy А.В., Kuznetsov S.A., Trunin Yu.V. Modeling of magnetic characteristics of switched reluctance machines. Herald of the Bauman Moscow State Technical University. Series Natural Sciences, 2007, no. 4(27), pp. 57–77. (in Russian)
  29. Le-Huy H., Brunelle P. Design and implementation of a switched reluctance motor generic model for simulink simpowersystems.Modeling and simulation of electric machines, converters and systems; Electrimatics 2005, 2005, pp. 1–35.
  30. Le-Huy H., Brunelle P. A versatile nonlinear switched reluctance motor model in Simulink using realistic and analytical magnetization characteristics. Proc. of the 31st Annual Conference of IEEE Industrial Electronics Society (IECON), 2005, pp. 1556–1561. https://doi.org/10.1109/iecon.2005.1569136


Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Copyright 2001-2024 ©
Scientific and Technical Journal
of Information Technologies, Mechanics and Optics.
All rights reserved.

Яндекс.Метрика