The Transactions of the Korean Institute of Power Electronics (전력전자학회논문지)

The Korean Institute of Power Electronics (전력전자학회)
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Study on Predicting Induction Motor Characteristics of Alternate QD Model Under Light Loads by Comparing Performance of MTPA Control

단위전류당최대토크 제어기의 성능 비교를 통한 경부하에서 대안모델의 유도전동기 동특성 예측에 관한 연구

  • Received : 2015.12.17
  • Accepted : 2016.01.04
  • Published : 2016.02.20
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Abstract

This study investigates a high-accuracy alternate QD model to estimate the characteristics of induction motor under light loads. To demonstrate the usefulness of the alternate QD model, a maximum torque per amp (MTPA) control based on the alternate model is shown to outperform MTPA control based on the standard QD model. The experimental study conducted in this work exhibits that the MTPA control based on the alternate QD model tracks torque commands between 20 Nm and 30 Nm with 5% error, whereas the MTPA control based on the standard QD model generates torques lower by over 23% compared with the aforementioned torque commands. This result indicates that the alternate QD model is a highly accurate model for induction motors under light loads.

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References

  1. P. C. Krause, O. Wasynczuk, and S. D. Sudhoff, "Analysis of electric machinery and drive systems," IEEE Press, 2002.
  2. O. Wasynczuk, S. D. Sudhoff, K. A. Corzine, J. L. Tichenor, P. C. Krause, I. G. Hansen, and L. M. Taylor, "A maximum torque per ampere control strategy for induction motor drives," IEEE Transactions on Energy Conversion, Vol. 13, No. 2, pp. 163-169, Jun. 1998. https://doi.org/10.1109/60.678980
  3. T. A. Najafabadi, F. R. Salmasi, and P. Jabehdar- Maralani, "Detection and isolation of speed-, DC-link voltage-, and current-sensor faults based on an adaptive observer in induction-motor," IEEE Transactions on Industrial Electronics, Vol. 58, No 5, pp. 1662-1672, 2011. https://doi.org/10.1109/TIE.2010.2055775
  4. R. J. Kerkman, "Steady-state and transient analyses of an induction machine with saturation of the magnetizing branch," IEEE Transactions on Industy Applications, Vol. 21, No 1, pp. 226-234, Jan/Feb. 1985.
  5. C. R. Sullivan and S. R. Sanders, "Models for induction machines with magnetic saturation of the main flux path," IEEE Transactions on Industy Applications, Vol. 31, No. 4, pp. 907-917, Jul/Aug. 1995. https://doi.org/10.1109/28.395303
  6. 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.
  7. T. A. Lip and A. Consoli, "Modeling of induction motors with saturable leakage reactances," IEEE Transactions on Industy Applications, Vol. 20, No 1, pp. 180-189, Jan/Feb. 1984.
  8. A. C. Smith, R. C. Healey, and 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, Mar. 1995.
  9. S. Moon, A. Keyhani, and S. Pillutla, "Nonlinear neural-network modelling of an induction machine," IEEE Transactions on Control Systems Technology, Vol. 7, No 2, pp. 203-211, Mar. 1999. https://doi.org/10.1109/87.748146
  10. 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, Jun. 2002. https://doi.org/10.1109/TEC.2002.1009469
  11. S. D. Sudhoff, D. C. Aliprantis, B. T. Kuhn, and P. L. Chapman, "Experimental characterization of an advanced induction machine model," 2005 IEEE Transactions on Energy Conversion, Vol. 18, pp. 48-56, Mar. 2003.
  12. C. Kwon and S. D. Sudhoff, "A genetic algorithm based induction machine characterization procedure," 2005 International Electric Machines and Drives Conference, pp. 1358-1364, May 2005.
  13. C. Kwon and S. D. Sudhoff, "An improved maximum torque per amp control for induction motor drives," In 20th annual IEEE Applied Power Electronics conference and Exposition, pp. 740-745, Mar. 2005.
  14. "Energy Systems Analysis Consortium (ESAC) Non-Encoded Genetic Algorithm Toolbox (ENEGAT) Ver 5.5," School of Electrical and Computer Engr., Purdue Univ., West Lafayette, IN, 47907, 2003.
  15. 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, Jan/Feb. 1994. https://doi.org/10.1109/28.273627