Skip to main content

Part of the book series: Studies in Computational Intelligence ((SCI,volume 327))

  • 1182 Accesses

Abstract

In this chapter a three-phase magnetic induction motor squirrel-cage is analyzed with the Finite Element Method (FEM). Five variations of the rotor geometry design are analyzed. The analysis has been made with simulations of static configurations. For each geometry an identification of the parametric model has been obtained. For the optimization of the parameters, Genetic Algorithms (GA) have been used as a robust optimization method.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Amuliu, B., Ali, K.: Identification of Variable Frequency Induction Motor Models From Operating Data. IEEE Transactions on Energy Conversion 17(1), 24–31 (2002)

    Article  Google Scholar 

  2. Belmans, R., Findlay, R.D., Geysen, W.: A Circuit Approach to Finite Element Analysis of a Double Squirrel Cage Induction Motor. IEEE Transactions on Energy Conversion 5(4), 719–724 (1990)

    Article  Google Scholar 

  3. Boonruang, M., Nittaya, M., Anant, O.: Dynamic Model Identification of Induction Motors using Intelligent Search Techniques with taking Core Loss into Account. In: 6th WSEAS International Conference on Power Systems, Lisbon, Portugal, pp. 108–115 (2006)

    Google Scholar 

  4. David, A., Gary, B.: Evolutionary Computation and Convergence to a Pareto Front, pp. 221–228. Stanford University, California (1998)

    Google Scholar 

  5. Haque, T., Nolan, R., Pillay, P., et al.: Parameter Determination for Induction Motors, pp. 45–49. IEEE, Los Alamitos (1994)

    Google Scholar 

  6. Harry, H., Charles, W.: Estimation of Induction Motor Parameters by Genetic Algorithm, pp. 21–28. IEEE, Los Alamitos (2003)

    Google Scholar 

  7. Lowther, D.A., Freeman, E.M.: Further aspects of the Kelvin transformation method for dealing with open boundaries. IEEE Transactions on Magnetics 28(2), 1667–1670

    Google Scholar 

  8. von Lücken, C.D.: Algoritmos Evolutivos para Optimización Multiobjetivo: un Estudio Comparativo en un Ambiente Paralelo Asíncrono. Universidad Nacional de Asunción (2003)

    Google Scholar 

  9. Meeker, D.: Induction Motor Example. IEEE, Los Alamitos (2002)

    Google Scholar 

  10. Mehmet, Ç., Ramazan, A.: Design optimization of induction motor by genetic algorithm and comparison with existing motor. Mathematical and Computational Applications 11(3), 193–203 (2006)

    Google Scholar 

  11. Mehmet, Ç., Ramazan, A., Osman, B.: Cost optimization of submersible motors using a genetic algorithm and a finite element method. Int. J. Adv. Manuf. Technol. 33, 223–232 (2006)

    Google Scholar 

  12. Mirafzal, B., Gary, L., Rangarajan, M.: Determination of Parameters in the Universal Induction Motor Model. IEEE Transaction on Industry Applications 45(1), 1207–1216 (2007)

    Google Scholar 

  13. Molinar, D., De Weerdt, R., Belmans, R., et al.: Calculation of two-axis induction motor model parameters using finite elements. IEEE, Los Alamitos (1996)

    Google Scholar 

  14. Nerg, J., Pyrhonen, J., Partanen, J.: Finite element modelling of the magnetizing inductance of an induction motor as a function of torque. IEEE Transactions on M 40(4), 2047–2049 (2004)

    Article  Google Scholar 

  15. Patrick, N., Anahita, Z., El-Sharkawi, M.A.: Pareto Multi Objective Optimization, pp. 84–91. IEEE, Los Alamitos (2005)

    Google Scholar 

  16. Phumiphak, T., Chat-Uthai, C.: Estimation of Induction Motor Parameters Based on Field Test Coupled with Genetic Algorithm, pp. 1199–1203. IEEE, Los Alamitos (2002)

    Google Scholar 

  17. Qiushi, C., Adalbert, K.: A Review of Finite Element Open Boundary Techniques for Static and Quasi-Static Electromagnetic Field Problems. IEEE Transactions on Magnetics 33(1), 663–676 (1997)

    Article  Google Scholar 

  18. Rasmus, K.U.: Models for Evolutionary Algoritms and Their Applications in System Identification and Control Optimization. University of Aarhus (2003)

    Google Scholar 

  19. Rasmus, K., Pierré, V.: Parameter identification of induction motors using stochastic optimization algorithms. Applied Soft. Computing 4, 49–64 (2004), doi:10.1016/j.asoc.2003.08.002

    Article  Google Scholar 

  20. Salon, S.J.: Finite Element Analysis of Electrical Machines. Kluwer Academic Publishers, Boston (1995)

    Google Scholar 

  21. Stochniol, A.: A General Transformation for Open Boundary Finite Element Method for Electromagnetic Problems. IEEE Transactions on Magnetics 28(2), 1679–1681 (1992)

    Article  Google Scholar 

  22. Tandom, S.C.: Finite Element Analysis of Induction Machines. IEEE, Los Alamitos (1982)

    Google Scholar 

  23. Wall, M.: GAlib documentation. MIT, Cambridge (2000), http://lancet.mit.edu/ga/dist/

    Google Scholar 

  24. Yamazaki, K.: An efficient procedure to calculate equivalent circuit parameters of induction motor using 3-D nonlinear time-stepping finite-element method. IEEE Transactions on Magnetics 38(2), 1281–1284 (2002)

    Article  Google Scholar 

  25. Yann, C.: Personal Website (2009), http://ycollette.free.fr

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Simón, L., Monzón, J.M. (2010). Parametric Identification of a Three-Phase Machine with Genetic Algorithms. In: Wiak, S., Napieralska-Juszczak, E. (eds) Computational Methods for the Innovative Design of Electrical Devices. Studies in Computational Intelligence, vol 327. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16225-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16225-1_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16224-4

  • Online ISBN: 978-3-642-16225-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics