DOI QR코드

DOI QR Code

A Study on the Optimization Strategy using Permanent Magnet Pole Shape Optimization of a Large Scale BLDC Motor

대용량 BLDC 전동기의 영구자석 형상 최적화를 통한 최적화 기법 연구

  • Received : 2009.11.23
  • Accepted : 2010.03.22
  • Published : 2010.05.01

Abstract

This paper presents a response surface method(RSM) with Latin Hypercube Sampling strategy, which is employed to optimize a magnet pole shape of large scale BLDC motor to minimize the cogging torque. The proposed LHS algorithm consists of the multi-objective Pareto optimization and (1+1) evolution strategy. The algorithm is compared with the uniform sampling point method in view points of computing time and convergence. In order to verify the developed algorithm, a 6 MW BLDC motor is simulated with 4 design parameters (arc length and 3 variables for magnet) and 4 constraints for minimizing of the cogging torque. The optimization procedure has two stages; the fist is to optimize the arc length of the PM and the second is to optimize the magnet pole shape by using the proposed hybrid algorithm. At the 3rd iteration, an optimal point is obtained, and the cogging torque of the optimized shape is converged to about 14% of the initial one. It means that 3 iterations aregood enough to obtain the optimal design parameters in the program.

Keywords

References

  1. 우성현, 정현구, 신판석, "민감도기법과 RSM을 이용한 대용량 BLDC 전동기 영구자석의 형상 최적화", 전기학회논문지, 58권 4호, 2009년 4월.
  2. Michael Stein, "Large Sample Properties of Simulations Using Latin Hypercube Sampling", Technometrics, Vol. 29, No. 2, pp.143-151, May 1987. https://doi.org/10.2307/1269769
  3. C. S. Koh, H. S. Yoon, K.W. Nam, and H. S. Choi, "Magnetic Pole Shape Optimization of Permanent Magnet Motor for Reduction of Cogging Torque," IEEE Trans. on Magn., vol. 33, no. 2, pp.1822-1827, March 1997. https://doi.org/10.1109/20.582633
  4. J.S.Ryu, Y.Yao, C. S. Koh, S. N. Yoon, and D. S. Kim, "Optimal shape design of 3-D nonlinear electromagnetic devices using parameterized design sensitivity analysis," IEEE Trans. on Magn., Vol. 41, No. 5, pp.1792-1795, May 2005. https://doi.org/10.1109/TMAG.2005.845982
  5. K. J. Han, H. S. Cho, D. H. Cho and H. K. Jung, "Optimal core shape design for cogging torque reduction of brushless DC motor using genetic algorithm," IEEE Trans. on Magn., vol. 36, no. 4, pp. 1927-1931, July 2000 https://doi.org/10.1109/20.877824
  6. C. A. Borghi, D. Casadei, A. Cristofolini, M. Fabbri, and G. Serra, "Application of a multiobjective in permanent magnet motors," IEEE Trans. on Magn., vol.35, no.5, pp.4238-4246, September 1999.minimization technique for reducing the torque ripple https://doi.org/10.1109/20.799073
  7. 大川光吉 (역:원종수), "페라이트 磁石回轉機의 設計", 동일출판사, 1995. 5.
  8. J. R. Hendershot Jr., TJE Miller "Design of Brushless Permanent-Magnet Motors", Magna Physics Publishing and Clarendon Press, Oxford, 1994.
  9. P. Alotto, and M.A. Nervi,"An efficient hybrid algorithm for the optimization of problems with several local minima," International Journal for umerical Methods in Engineering, Vol.50, pp.847-868, 2001. https://doi.org/10.1002/1097-0207(20010210)50:4<847::AID-NME54>3.0.CO;2-Q
  10. Koehler J.R. and Owen A.B., Computer Experiments, Handbook of Statistics, Elsevier Science, New York, pp.261-308, 1996.
  11. Yanli Zhang, H.S. Yoon and C.S. Koh, "Study on a Robust Optimization Algorithm Using Latin Hypercube Sampling Experiment and Multiquadric Radial Basis Function," Proceeding of KIEE EMECS Annual Spring Conference, pp.162-164, April 2007.
  12. D. Tsao, and J. Webb, "Construction of device performance models using adaptive interpolation and sensitivities", IEEE Trans. on Magn., Vol. 41, No. 5, pp. 1768-1771, May 2005. https://doi.org/10.1109/TMAG.2005.845997