• DocumentCode
    41431
  • Title

    Integrated High-Frequency Coaxial Transformer Design Platform Using Artificial Neural Network Optimization and FEM Simulation

  • Author

    Li, Jeffrey ; water, Wayne ; Boyuan Zhu ; Junwei Lu

  • Author_Institution
    Queensland Micro- & Nanotechnol. Centre, Griffith Univ., Nathan, QLD, Australia
  • Volume
    51
  • Issue
    3
  • fYear
    2015
  • fDate
    Mar-15
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    Designing a high-frequency power transformer is a complicated task due to its multiple interrelation design procedures, large number of variables, and other relevant factors. Traditional transformer design relies on manual paper work and personal experience, which requires engineering design man-hours and long delivery cycles. In this paper, a developed transformer computer design environment is addressed. It helps engineers to automatically model, simulate, and optimize transformer design using an artificial neural network algorithm and the finite-element method, and delivers a reliable design result. Utilizing the proposed platform, an 8 kW coaxial transformer is successfully designed, tested, and manufactured.
  • Keywords
    finite element analysis; high-frequency transformers; neural nets; optimisation; power engineering computing; power transformers; reliability; FEM simulation; artificial neural network optimization; finite element method; integrated high-frequency coaxial power transformer design platform; multiple interrelation design reliability; power 8 kW; transformer computer design environment; Artificial neural networks; Databases; Finite element analysis; Magnetics; Power transformers; Windings; Wires; Artificial neural network (ANN); finite-element method (FEM); high-frequency (HF) transformer; transformer design platform;
  • fLanguage
    English
  • Journal_Title
    Magnetics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0018-9464
  • Type

    jour

  • DOI
    10.1109/TMAG.2014.2368123
  • Filename
    7093514