AC resistance Prediction of Litz Wire Planer Spiral Coil Based on Litz wire Loss Model

S. Kawahara, Kazuhiro Umetani, E. Hiraki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The Litz wire is utilized to wireless power transfer system and induction heating according to has small AC resistance in high frequency. Prediction of AC resistance of the Litz wire is important for design optimization of the Litz wire, hence the recent study has proposed analytical AC resistance prediction model of the Litz wire. However, verification in practical coils using the Litz wire is still insufficient. The purpose of this paper is to verify the prediction accuracy of AC resistance using a full analytical model in a practical coil. For practical coil, planer spiral coils are selected, and AC resistance of the planer spiral coil is calculated by combining with the loss model and the FEM analysis. As a result, the Litz wire loss model is found to well predict the measured AC resistance of the Litz wire planer spiral coil, supporting the appropriateness of the Litz wire loss model.

Original languageEnglish
Title of host publication23rd International Conference on Electrical Machines and Systems, ICEMS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1541-1546
Number of pages6
ISBN (Electronic)9784886864192
DOIs
Publication statusPublished - Nov 24 2020
Event23rd International Conference on Electrical Machines and Systems, ICEMS 2020 - Hamamatsu, Japan
Duration: Nov 24 2020Nov 27 2020

Publication series

Name23rd International Conference on Electrical Machines and Systems, ICEMS 2020

Conference

Conference23rd International Conference on Electrical Machines and Systems, ICEMS 2020
CountryJapan
CityHamamatsu
Period11/24/2011/27/20

Keywords

  • Copper loss
  • Finite-element method (FEM)
  • Litz wire
  • Proximity effect

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Safety, Risk, Reliability and Quality
  • Control and Optimization

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