Advertisement

Journal of Mechanical Science and Technology

, Volume 33, Issue 1, pp 173–182 | Cite as

Optimal design method for the structural parameters of hybrid magnetic coupler

  • Shuang Wang
  • Kun Hu
  • De-yong Li
Article
  • 3 Downloads

Abstract

In order to solve the problem of small transmission power and large space occupation of the magnetic vortex coupler, a hybrid magnetic coupler is proposed. A 3D magnetic field finite element distribution model was built according to the effects of the structural parameters of this hybrid magnetic coupler on its dynamic performance, its structural parameters were optimized by an improved response surface methodology (IRSM), and then the correctness of these optimized parameters was verified in a self-designed test. The structural parameters of this hybrid magnetic coupler were optimized using IRSM, the optimization results showing that the magnetic flux density in this hybrid magnetic coupler increased by 5.01 times. According to the test results, the maximum error between the test value and the optimal value of maximum torque, average output speed and slip is 11.9 %, 5.3 % and 9.7 %, respectively, suggesting that this optimization method is tenable. The results could serve as theoretical and technical bases for the design of hybrid magnetic couplers.

Keywords

Hybrid magnetic coupler Structural parameter optimization design Improved response surface methodology Dynamic performance Test verification 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. [1]
    C. Chen, S. Hagemann and J. Liu, Assessment of impact of climate change on the blue and green water resources in large river basins in China, Environmental Earth Sciences, 8 (2015) 1–14.Google Scholar
  2. [2]
    A. Matzarakis and D. Fröhlich, Sport events and climate for visitors—the case of FIFA World Cup in Qatar 2022, International Journal of Biometeorology, 59 (4) (2015) 481–486.CrossRefGoogle Scholar
  3. [3]
    L. L. Wang, L. M. Yang and Y. Y. Ding, On the energy conservation and critical velocities for the propagation of a “steady-shock” wave in a bar made of cellular material, Acta Mechanica Sinica, 29 (3) (2013) 420–428.MathSciNetCrossRefzbMATHGoogle Scholar
  4. [4]
    H. E. Fujun et al., Research on characteristics of permanent magnet Eddy-current coupling drive, Journal of Mechanical Engineering, 52 (8) (2016) 23–28.CrossRefGoogle Scholar
  5. [5]
    B. J. Tillotson, E. Loth and J. C. Dutton, Experimental study of a mach 3 bump compression flowfield, Acta Mechanica Sinica, 11 (4) (2015) 1–14.Google Scholar
  6. [6]
    A. Skarlatos and T. Theodoulidis, Analytical treatment of Eddy-current induction in a conducting half-space with a cylindrical hole parallel to the surface, IEEE Transactions on Magnetics, 47 (11) (2011) 4592–4599.CrossRefGoogle Scholar
  7. [7]
    C. Camerini et al., Eddy current techniques for super duplex stainless steel characterization, Journal of Magnetism & Magnetic Materials, 388 (2015) 96–100.CrossRefGoogle Scholar
  8. [8]
    T. Lubin, S. Mezani and A. Rezzoug, Experimental and theoretical analysis of axial magnetic coupling under steady-state and transient operation, IEEE Transactions on Industrial Electronics, 61 (8) (2014) 4356–4365.CrossRefGoogle Scholar
  9. [9]
    S. Hogberg et al., Parametric design optimization of a novel permanent magnet coupling using finite element analysis, IEEE Energy Conversion Congress and Exposition (2014) 1465–1471.Google Scholar
  10. [10]
    A. Canova and B. Vusini, Design of axial eddy-current couplers, IEEE Transactions on Industry Applications, 39 (3) (2003) 725–733.CrossRefGoogle Scholar
  11. [11]
    A. Canova et al., Genetic optimisation of radial eddy current couplings, COMPEL-The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 24 (3) (2005) 767–783.CrossRefzbMATHGoogle Scholar
  12. [12]
    M. Raisee, D. Kumar and C. Lacor, A non-intrusive model reduction approach for polynomial chaos expansion using proper orthogonal decomposition, International Journal for Numerical Methods in Engineering, 103 (4) (2015) 293–312.MathSciNetCrossRefzbMATHGoogle Scholar
  13. [13]
    J. E. Dolbow and A. Devan, Enrichment of enhanced assumed strain approximations for representing strong discontinuities: Addressing volumetric incompressibility and the discontinuous patch test, International Journal for Numerical Methods in Engineering, 59 (1) (2004) 47–67.CrossRefzbMATHGoogle Scholar
  14. [14]
    B. Suleiman and De Suvranu, Development of a genetic algorithm-based lookup table approach for efficient numerical integration in the method of finite spheres with application to the solution of thin beam and plate problems, International Journal for Numerical Methods in Engineering, 67 (12) (2006) 1700–1729.MathSciNetCrossRefzbMATHGoogle Scholar
  15. [15]
    A. Amirjanov, Investigation of a changing range genetic algorithm in noisy environments, International Journal for Numerical Methods in Engineering, 73 (1) (2008) 26–46.MathSciNetCrossRefzbMATHGoogle Scholar
  16. [16]
    E. E. Gdoutos, R. Agrawal and H. D. Espinosa, Comparison of the Ewald and Wolf methods for modeling electrostatic interactions in nanowires, International Journal for Numerical Methods in Engineering, 84 (13) (2010) 1541–1551.CrossRefzbMATHGoogle Scholar
  17. [17]
    S. Toro et al., A two-scale failure model for heterogeneous materials: Numerical implementation based on the finite element method, International Journal for Numerical Methods in Engineering, 97 (5) (2014) 313–351.MathSciNetCrossRefzbMATHGoogle Scholar
  18. [18]
    R. J. Lian, Adaptive self-organizing fuzzy sliding-mode radial basis-function neural-network controller for robotic systems, IEEE Transactions on Industrial Electronics, 61 (3) (2014) 1493–1503.CrossRefGoogle Scholar
  19. [19]
    A. Belayneh et al., Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet neural network and wavelet support vector regression models, Journal of Hydrology, 508 (2) (2014) 418–429.CrossRefGoogle Scholar
  20. [20]
    S. Yunkang and Y. Hui-ping, Improvement of response surface method and its application to engineering optimization, Science Press (2011).Google Scholar

Copyright information

© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Anhui Mine Electromechanical Equipment Cooperative Innovation CenterAnhui University of Science and TechnologyHuainanChina

Personalised recommendations