An On-line Rotor Resistance Estimator for Induction Machine Drives

  • Kwon, Chun-Ki (Dept. of Medical IT Engineering, Soonchunhyang University)
  • Published : 2009.05.20

Abstract

Rotor resistance variation due to changing rotor temperature is a significant issue in the design of induction motor controls. In this work, a new on-line rotor resistance estimator is proposed based on an alternate qd induction machine model which provides better mathematical representation of an induction machine than the classical qd model (which uses constant parameters). This is because the former simultaneously includes leakage saturation, magnetizing path saturation, and distributed circuit effects in the rotor conductors. The comparisons via computer simulation studies show the ability of the proposed estimator to accurately track rotor resistance variation. For the experimental studies, due to the difficulty in measuring the actual rotor resistance, comparison of the controller performance using the proposed estimator, the classical qd model based estimator, and no estimator is made.

Keywords

References

  1. B. karanavil, M.F. Rahman, and C. Grantham, "Implementation of an on-line resistance estimation using arfitificial neural networks for vector controlled induction motor drive," The 29th Annual Conference of the IEEE Industrial Electronics Society, Vol. 2, pp. 1703-1708, Nov., 2003
  2. M. Benhaddadi, K. Yazid, and R. Khaldi, "An Effective Identification of Rotor Resistance for Induction Motor Vector Control," IEEE Instrumentation and Measurement Technology Conference, Vol. 1, pp. 339-342, May 1997
  3. Y. Miloud and A. Draou, "Fuzzy Logic Based Rotor Resistance Estimator of an Indirect Vector Controlled Induction Motor Drive," IEEE Industrial Electronics Society, IECON02, Vol. 2, pp.961-966, Nov., 2002
  4. M.A. Ouhrouche, "Vector Control of an Induction Motor With On-line Rotor Resistance Identification," Proceedings of the 1999 IEEE Canadian Conference on Electrical and Computer Engineering Shaw Conference Center, Edmonton, Alberta, Canada, pp. 1121-1125, May, 1999
  5. F. Zidani, M.S. Nait-Said, M.E.H. Benbouzid, D. Diallo, and R. Abdessemed, "A Fuzzy Rotor Resistance Updating Scheme for an IFOC Induction Motor Drive," IEEE Power Engineering Review, pp. 47-50, Nov., 2001
  6. S. Halasz, B.T. Huu, and K. Veszpremi, "Rotor Time Constant On-line Identification For Field Oriented AC Drive," Proceedings of the IEEE International Symposium, Vol. 2, pp. 654-659, July 1995, pp. 654-659, 1995
  7. C. Gonzalez, J. Arribas, and D. Prieto, "Optimal Regulation of Electric Drives With Constant Load Torque," IEEE transactions on Industrial Electronics, Vol. 53, No. 6, pp. 1762-1769, December 2006 https://doi.org/10.1109/TIE.2006.885121
  8. G. Bartolini, A. Pisano, and P. Pisu, "Simplified Exponentially Convergent Rotor Resistance Estimation for Induction Motors," IEEE Transactions on Automatic Control, Vol. 48, No. 2, pp. 325-330, Feb., 2003 https://doi.org/10.1109/TAC.2002.808493
  9. S.K. Jeong, Z.G. Lee, H.A. Toliyat, and P. Niazi, "Sensorless Control of Induction Motors With Simultaneous On-line Estimation Of Rotor Resistance and Speed Based on the Feedforward Torque Control Scheme," IEEE International Electric Machines and Drives conference, Vol. 3, pp. 1837-1842, June 2003
  10. A. Miloudi and A. Draou, "Variable Gain PI Controller Design For Speed Control and Rotor Resistance Estimation of an Indirect Vector-controlled Induction Machine Drive," IEEE 2002 28th Annual Conference of the Industrial Electronics Society, Vol. 1, pp. 323-328, Nov., 2002
  11. B. Karanayil, M. F. Rahman, and C. Grantham, "Online Stator and Rotor Resistance Estimation Scheme Using Artificial Neural Networks for Vector Controlled Speed Sensorless Induction Motor Drive," IEEE transactions on Industrial Electronics, Vol. 54, No. 1, pp. 167-176., February 2007 https://doi.org/10.1109/TIE.2006.888778
  12. A. B. Proca and A. Keyhani, "Sliding-Mode Flux Observer With Online Rotor Parameter Estimation for Induction Motors," IEEE transactions on Industrial Electronics, Vol. 54, No. 2, pp. 716-723, April 2007 https://doi.org/10.1109/TIE.2007.891786
  13. R. J. Kerkman, "Steady-state and transient analyses of an induction machine with saturation of the magnetizing branch," IEEE Transactions on Industry Applications, Vol. 21, No. 1, pp. 226-234, Jan/Feb, 1985 https://doi.org/10.1109/TIA.1985.349684
  14. C. R. Sullivan, S. R. Sanders, "Models for induction machines with magnetic saturation of the main flux path," IEEE Transactions on Industry Applications, Vol. 31, No. 4, pp. 907-917, July/August, 1995 https://doi.org/10.1109/28.395303
  15. J. Langheim, "Modelling of rotorbars with skin effect for dynamic simulation of induction machines," Conference Record of the 1989 IEEE Industry Applications Society Annual Meeting, pp. 38-44, 1989
  16. T. A. Lipo, A. Consoli, "Modeling of induction motors with saturable leakage reactances," IEEE Transactions on Industry Applications, Vol. 20, No. 1, pp. 180-189, Jan/Feb. 1984 https://doi.org/10.1109/TIA.1984.4504392
  17. A. C. Smith, R. C. Healey, S. Williamson, "A transient induction motor model including saturation and deep bar effect," IEEE Transactions on Energy Conversion, Vol. 11, No. 1, pp. 8-15, March, 1995 https://doi.org/10.1109/60.486570
  18. S. Moon, A. Keyhani, S. Pillutla, "Nonlinear neural-network modeling of an induction machine," IEEE Transactions on Control Systems Technology, Vol. 7, No. 2, pp. 203-211, March, 1999 https://doi.org/10.1109/87.748146
  19. C. Kwon, S. D. Sudhoff, "An Improved Maximum Torque Per Amp Control for Induction Machine Drives," in 20th Annual IEEE Applied Power Electronics Conference and Exposition, pp. 740-745, March, 2005
  20. S. D. Sudhoff, D. C. Aliprantis, B. T. Kuhn , and P. L. Chapman, "An Induction Machine Model for Predicting Inverter – Machine Interaction," IEEE Transactions on Energy Conversion, Vol. 17, pp. 203-210, June 2002 https://doi.org/10.1109/TEC.2002.1009469
  21. S. D. Sudhoff, P. L. Chapman, D. C. Aliprantis, and B. T. Kuhn, "Experimental Characterization of an Advanced Induction Machine Model," IEEE Transactions on Energy Conversion, Vol. 18, pp. 48-56, March 2003 https://doi.org/10.1109/TEC.2002.808333
  22. C. Kwon, S. D. Sudhoff, "A Genetic Algorithm Based Induction Machine Characterization Procedure with Application to Maximum Torque Per Amp Control," IEEE transaction on Energy Conversion, Vol. 21, No. 2, June 2006
  23. P. C. Krause, O. Wasynczuk, S. D. Sudhoff, Analysis of Electric Machinery and Drive Systems, IEEE Press, 2002
  24. C. Kwon, S. D. Sudhoff, "An Adaptive Maximum Torque Per Amp Control Strategy," the 2005 International Electric Machines and Drives Conference, pp. 783-788, May 2005
  25. P. L. Jansen and R. D. Lorenz, "A Physically Insightful Approach to the Design and Accuracy Assessment of Flux Observer for Field Oriented Induction Machine Drives," IEEE Transactions on Industry Applications, Vol. 30, No. 1, pp. 101-110, January/February 1994 https://doi.org/10.1109/28.273627
  26. J. Kim, J. Choi, and S. Sul, "Novel Rotor Flux Observer Using Observer Characteristic Function in Complex Vector Space for Field Oriented Induction Motor Drives," IEEE transactions on Industry Applications, Vol. 38, pp. 1334-1443, September/October 2002 https://doi.org/10.1109/TIA.2002.802994