High frequency transformer design for specific static magnetising and leakage inductances using combination of multi-layer perceptron neural networks and FEM simulations

Parham Mohammadi, Rahim Samanbakhsh, Peyman Koohi, Federico Ibanez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Power industry is evolving toward high density power and therefore high frequency applications. Converters with low switching losses based on soft switching have been developed. In many of these converters, the transformers that are used, should have tuned magnetizing and leakage inductances. Hence, more accurate design methodologies should be developed. In this paper air-gap, winding overlap coefficient and core geometry are used for designing high frequency transformer with desired magnetizing and leakage inductances. Core geometry is a concept that is used by manufactures to select cores based on their power-handling capability. In this paper, instead of using complex analytical methods or time consuming and expensive FEM simulations, a methodology is proposed that uses few FEM simulations and multi-layer perceptron neural networks for designing specific magnetizing and leakage inductances, for a wide selection of cores. Moreover, the effect of core geometry on magnetizing and leakage inductances is explored. Detailed 3D-FEM simulations confirm the validity of proposed methodology. In addition, a prototype was tested and experimental results are consistent with Neural-network results.

Original languageEnglish
Title of host publicationPEDG 2019 - 2019 IEEE 10th International Symposium on Power Electronics for Distributed Generation Systems
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages837-842
Number of pages6
ISBN (Electronic)9781728124551
DOIs
Publication statusPublished - Jun 2019
Event10th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2019 - Xi'an, China
Duration: 3 Jun 20196 Jun 2019

Publication series

NamePEDG 2019 - 2019 IEEE 10th International Symposium on Power Electronics for Distributed Generation Systems

Conference

Conference10th IEEE International Symposium on Power Electronics for Distributed Generation Systems, PEDG 2019
Country/TerritoryChina
CityXi'an
Period3/06/196/06/19

Keywords

  • FEM
  • Neural-Networks
  • Soft switching
  • Transformers

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