DOI QR코드

DOI QR Code

Parameter Estimation of Three-Phase Induction Motor by Using Genetic Algorithm

  • Jangjit, Seesak ;
  • Laohachai, Panthep
  • Published : 2009.09.01

Abstract

This paper suggests the techniques in determining the values of the steady-state equivalent circuit parameters of a three-phase induction machine using genetic algorithm. The parameter estimation procedure is based on the steady-state phase current versus slip and input power versus slip characteristics. The propose estimation algorithm is of non-linear kind based on selection in genetic algorithm. The machine parameters are obtained as the solution of a minimization of objective function by genetic algorithm. Simulation shows good performance of the propose procedures.

Keywords

parameter estimation;induction motor;genetic algorithm

References

  1. S. Ansuj and, F. Shokooh, and R. Schinzingger, 'Parameter Estimation for Induction Machines Based on Sensitivity Analysis,' IEEE Transl, on industry application, .vol. 25, no 6, pp. 1035-1040 https://doi.org/10.1109/28.44239
  2. Dong Hwa Kim, and Jea Hoon Cho, 'Parameter Estimation of a squirrel-Double Cage Induction Motor Using Clonal Selection of Immune Algorithm,' IEEE Industrial Electronics Society, Busan, Korea, p. 1190-1194
  3. P.Vaclavek and P. Blaha, 'Lypunov-Function-Based Flux and Speed Observer for AC Induction Motor Sensorless Control and Parameters Estimation,' IEEE Transl, on industry Electronics, .vol. 53, no 1, pp. 138-145 https://doi.org/10.1109/TIE.2005.862305
  4. M. Calvo and O.P. Malik, 'Synchronous Machine Steady-State Parameter Estimation Using Neural Networks,' IEEE Transl, on Energy Conversion, .vol. 19, no 2, pp. 237-244 https://doi.org/10.1109/TEC.2004.827041
  5. D. J. Atkinson, P. P. Acarnley, and J.W. Finch, 'Observers for Induction Motor State and Parameter Estimation,' IEEE Transl, on industry Applications, vol. 27, no 6, pp. 1119-1127 https://doi.org/10.1109/28.108463
  6. K. Wang, J Chiasson, M. Bodson, and L.M. Tolbert, 'A Nonlinear Least-Squares Approach for Identification of the Induction Motor Parameters,' Proc. 43th IEEE Conference on Decision and Control, December 14-17, 2004, Atlantis, Paradise Island, Bahamas, pp. 3856-3861
  7. G. K. Stefopoulos, P .S. Georgilakis, N.D.Hatziargyriou, and A .P. Sakis Meliopoulos, 'A Genetic Algorithm Solution to the Governor-Turbine Dynamic Model Identification in Multi-Machine Power System,' Proc. 44th IEEE Conference on Decision and Control, and the European Control Conference 2005, December 12-15, 2005, pp. 1288-1294
  8. Z.Michalewicz, Genetic Algorithms + Data Structures = Evolution Programs. New York: Springer-Verlag, 1996

Cited by

  1. Multi-Objective Optimal Design of a NEMA Design D Three-phase Induction Machine Utilizing Gaussian-MOPSO Algorithm vol.9, pp.1, 2014, https://doi.org/10.5370/JEET.2014.9.1.184
  2. Intuitionistic fuzzy $$c$$ c -means clustering algorithm with neighborhood attraction in segmenting medical image vol.19, pp.2, 2015, https://doi.org/10.1007/s00500-014-1264-2
  3. A Study on Fast Maximum Efficiency Control of Stator-Flux-oriented Induction Motor Drives vol.6, pp.5, 2011, https://doi.org/10.5370/JEET.2011.6.5.626