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2011-07-14
Application of Genetic Algorithms to Core Loss Coefficient Extraction
By
Progress In Electromagnetics Research M, Vol. 19, 133-146, 2011
Abstract
Core loss data are usually provided in the form of tables or curves of total loss versus flux density or frequency for electrical machine designers. These tables or curves can be used to extract the loss coefficients of the core loss formulas because accurate calculations of the coefficients have an important issue in electrical machine design. In this study, using original loss data given for M19 steel material, the core loss coefficients are calculated by the genetic algorithm developed in Matlab environment and electromagnetic analysis software (Ansoft Maxwell) is also used to extract the core loss coefficients in order to verify the proposed method. It is found that the exponent of flux density (B) depends on the flux range or the frequency range and these changes in the exponent of B can be correlated to the physical phenomenon of domain wall movement in response to an external field. As a difference from existing studies in literature, this study suggests a new method for extracting the core loss coefficients without any requirement for mathematical operations due to the nature of genetic algorithms and over the range of frequencies between 50-400 Hz and flux densities from 0 to 1.5 T, the new method yields lower errors for the specific core losses than those obtained by the magnetic field analysis software.
Citation
Nihat Ozturk, and Emre Celik, "Application of Genetic Algorithms to Core Loss Coefficient Extraction," Progress In Electromagnetics Research M, Vol. 19, 133-146, 2011.
doi:10.2528/PIERM11051310
References

1. Haupt, R. L. and D. H. Werner, Genetic Algorithms in Electromagnetic, IEEE Press, 2007.
doi:10.1002/047010628X

2. Haupt, R. L. and S. E. Haupt, Practical Genetic Algorithms, 2nd edition, Wiley-Interscience Pub., John Wiley & Sons, INC., New York, 2004.

3. Gen, M. and R. Cheng, "A survey of penalty techniques in genetic algorithms," Proceedings of IEEE International Conference on Evolutionary Computation, 804-809, May 20-22, 1996.

4. Fiorillo, F. and A. Novikov, "An improved approach to power losses in magnetic laminations under nonsinusoidal induction waveform," IEEE Transactions on Magnetics, Vol. 26, No. 5, 2904-2910, 1990.
doi:10.1109/20.104905

5. Landgraf, F. J. G., J. C. Teixeira, M. Emura, M. F. de Campos, and C. S. Muranaka, "Separating components of the hysteresis loss of non-oriented electrical steels," Materials Science Forum, Vol. 302-303, 440-445, 1999.
doi:10.4028/www.scientific.net/MSF.302-303.440

6. Chen, Y. and P. Pillay, "An improved formula for lamination core loss calculations in machines operating with high frequency and high flux density excitation," 37th IAS Annual Meeting Industry Applications Conference, Vol. 2, 759-766, 2002.

7. Boglietti, A., A. Cavagnino, M. Lazzari, and M. Pastorelli, "Predicting iron losses in soft magnetic materials with arbitrary voltage supply: An engineering approach," IEEE Transactions on Magnetics, Vol. 39, No. 2, 981-989, 2003.
doi:10.1109/TMAG.2003.808599

8. Yang, F., M. Rong, Z. Sun, Y. Wu, and W. Wang, "A numerical study of arc-splitting processes with eddy-current effects," 17th International Conference on Gas Discharges and Their Applications, 2008, GD 2008, 197-200, 2008.

9. Mohammed, O. A. and G. F. Uler, "A hybrid technique for the optimal design of electromagnetic devices using direct search and genetic algorithms," IEEE Transactions on Magnetics, Vol. 33, No. 2, 1931-1934, 1997.
doi:10.1109/20.582670

10. Ridley, R. and A. Nace, "Modeling ferrite core losses," Switching Power Magazine, 8-9, Winter, 2002.

11. Ionel, M. D., M. Popescu, S. J. Dellinger, R. J. Heideman, and M. I. McGilp, "On the variation with flux and frequency of the core loss coe±cients in electrical machines," IEEE Transactions on Industry Applications, Vol. 42, No. 3, 658-667, 2006.
doi:10.1109/TIA.2006.872941

12., Technical Datasheet for Core Material of Sura, http://www.sura.se/Sura/hp products.nsf/vOpendocument/03A8B2433FAE16C4C1 256AA8002280E6/$FILE/270-50.pdf?OpenElement, Feb. 22, 2011.
doi:10.1109/TIA.2006.872941

13. Abu-Al-Nadi, D. I., M. J. Mismar, and T. H. Ismail, "Genetically evolved phase-aggregation technique for linear arrays control," Progress In Electromagnetics Research, Vol. 43, 287-304, 2007.

14. Meng, Z., "Autonomous genetic algorithm for functional optimization," Progress In Electromagnetics Research, Vol. 72, 253-268, 2007.
doi:10.2528/PIER07031506

15. Mitchell, M., An Introduction to Genetic Algorithms, 5th edition, A Bradford Book the MIT Press, London, 1999.

16. Harik, G. R., F. G. Lobo, and D. E. Goldberg, "The compact genetic algorithm," IEEE Transactions on Evolutionary Computation, Vol. 3, No. 4, 287-297, 1999.
doi:10.1109/4235.797971

17. Elmas, C. and T. Yigit, "Genetic algorithm based on-line tuning of a pi controller for a switched reluctance motor drive," Electric Power Components and Systems, Vol. 35, No. 6, 675-691, 2007.
doi:10.1080/15325000601139674

18. Barranger, J., "Hysteresis and eddy current losses of a transformer lamination viewed as an application of the Poynting theorem," NASA Technical Note, Lewis Research Center, Cleveland, Ohio, Nov. 1965.