DOI QR코드

DOI QR Code

Study on Performance of Adaptive Maximum Torque Per Amp Control in Induction Motor Drives at Light Load Operation

  • Kwon, Chun-Ki (Dept. of Medical Information Technology Engineering, Soonchunhyang University) ;
  • Kong, Yong-Hae (Dept. of Medical Information Technology Engineering, Soonchunhyang University) ;
  • Kim, Dong-Sik (Dept. of Electrical Engineering, Soonchunhyang University)
  • Received : 2016.02.09
  • Accepted : 2016.08.18
  • Published : 2017.01.02

Abstract

Efficient operation of induction motor at light loads has been getting wide attention recently because the operating of induction motor at light loads occupies big portion of its operating regions in many applications such as environment friendly vehicle. As one of approaches to improve efficiency, Adaptive Maximum Torque Per Amp (Adaptive MTPA) control for induction motor drives has been proposed to achieve a desired torque with the minimum possible stator current. However, the Adaptive MTPA control was validated only at heavy load where, in general, control scheme tends to perform better than at light loads since the error in measurement of sensors is lower and signal to noise is better. Thus, although the performance of a control scheme is good at rated operating point, its performance at light load is somewhat in doubt in practice. This has led to considerable interest in efficiency of Adaptive MTPA control at light loads. This work experimentally demonstrates performance of Adaptive MTPA control at light loads regardless of rotor resistance variation, thus showing its good performance over all operating conditions.

Keywords

References

  1. Y. Zhang, "Induction Motor with Adjustable Windings for High Efficiency Drive in Light Load Operation," Journal of Electrical Engineering, Vol. 9, No.2, 2014, pp. 508-513.
  2. M. Farasat, A. Trzynadlowski, M. Fadali, "Efficiency improved sensorless control scheme for electric vehicle Induction Motors," IET Electrical Systems in Transportaion, Dec 2014, pp. 122-131.
  3. F. Ferreira, J. Simoes, J. Oliverira, "Novel Electronic Device to Improve the Performance of Variable-Torque Fixed-Speed Induction Motors," 2015 9th International Conference on Compatibility and Power Electronics (CPE), 2015, pp. 281-288.
  4. A. Odhano, R. Bojoi, A. Boglietti, S. Rosu, G. Griva, "Maximum Efficiency per Torque Direct Flux Vector Control of Induction Motor Drives," IEEE transactions on Industry Applications, Vol. 51, No. 6, 2015, pp. 4415-4424. https://doi.org/10.1109/TIA.2015.2448682
  5. Y. Liu and A. Bazzi, "A comprehensive Analytical Power Loss Model of an Induction Motor Drive System with Loss Minimization Control," 2015 IEEE International Electric Machines & Drives Conference(IEMDC), May 2015, pp. 1638-1643
  6. X. Fu and S. Li, "A Novel Neural Network Vector Control Technique for Induction Motor Drive," IEEE Transactions on Energy Conversion, Vol. 30, No. 4, Dec 2015, pp.1428- 1437 https://doi.org/10.1109/TEC.2015.2436914
  7. C. Kwon, "Study on Optimal Condition of Adaptive Maximum Torque Per Amp Controlled Induction Motor", Journal of Electrical Engineering Technology, Vol. 9, No. 1, January, 2014, pp. 231-238. https://doi.org/10.5370/JEET.2014.9.1.231
  8. C. Kwon, "Study on an Adaptive Maximum Torque Per Amp Control Strategy for Induction Motor Drives," Journal of Electrical Engineering & Technology, Vol. 8, No. 1, 2013, pp. 110-117. https://doi.org/10.5370/JEET.2013.8.1.110
  9. 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, June 1998, pp. 163-169. https://doi.org/10.1109/60.678980
  10. S. Krim, S. Gdaim, A. Mtibaa, M. Mimouni, "Design and Implementation of Direct Torque Control Based on an Intelligent Technique of Induction Motor on FPGA," Journal of Electrical Engineering, Vol. 10, No. 4, 2015, pp. 1527-1539.
  11. I. Jeong, W. Choi, K. Park, "Sensorless Vector Control of Induction Motors for Wind Energy Applications Using MRAS and ASO", Journal of Electrical Engineering Technology, Vol. 9, No. 3, 2014, pp. 873-881. https://doi.org/10.5370/JEET.2014.9.3.873
  12. M. Comanescu, "A Robust Sensorless Sliding Mode Observer with Speed Estimate for the Flux Magnitude of the Induction Motor Drive," 2015 9th International conference on Compatibility and Power Electronics (CPE), 2015, pp. 224-229.
  13. S. Jurkovic, K. Rahman, J. Morgante, P. Savagian, "Induction Machine Design and Analysis for General Motors e-Assist Electrification," IEEE Transaction on Industry Applications, Vol. 51, No. 1, Jan/Feb 2015, pp. 631-639. https://doi.org/10.1109/TIA.2014.2330057
  14. S. D. Sudhoff, P. L. Chapman, D. C. Aliprantis, and B. T. Kuhn, "Experimental Characterization Procedure for Use with of an Advanced Induction Machine Model," IEEE Transactions on Energy Conversion, Vol. 18, Mar 2003, pp. 48-56. https://doi.org/10.1109/TEC.2002.808333
  15. 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, June 2002, pp. 203-210 https://doi.org/10.1109/TEC.2002.1009469
  16. C. Kwon, S. D. Sudhoff, "Genetic Algorithm-Based Induction Machine Characterization Procedure With Application to Maximum Torque Per Amp Control," IEEE Transactions on Energy Conversion, Vol. 21, June 2006, pp. 405-415 https://doi.org/10.1109/TEC.2006.874224
  17. P. C. Krause, O. Wasynczuk, S. D. Sudhoff, Analysis of Electric Machinery and Drive Systems, IEEE Press, 2002.
  18. "Energy Systems Analysis Consortium (ESAC) Genetic Optimization System Engineering Tool (GOSET) Ver 1.02," School of Electrical and Computer Engr., Purdue Univ., West Lafayette, IN, 47907, 2003.
  19. C. Kwon, S. D. Sudhoff, "An On-line Rotor Resistance Estimator for Induction Machine Drives," the 2005 International Electric Machines and Drives Conference, May 2005, pp. 391-397.