Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms

Chin Lung Yang, Shao Ping Cheng, Chung En Yu

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

Abstract

Fused helical and spiral (FHS) coils are proposed to improve the efficiency of wireless power transfer by using both neural network and generic algorithms. FHS coils take advantages of balancing the coupling coefficient and the quality factor. Moreover, neural network and generic algorithm are applied to optimize the structure and parameters of the FHS coils with variable pitches. From simulation, the proposed 3.25-mm FHS coil structure consists of three layers of 15 turns. The pitches of three layers are 0.075, 0.225, 0.3 mm, respectively. Due to more condensed magnetic field distribution, the power transmission efficiency is improved to 24% compared with traditional signal turn coil at distance of 20 mm.

Original languageEnglish
Title of host publication2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2537-2538
Number of pages2
ISBN (Electronic)9781538671023
DOIs
Publication statusPublished - 2018 Jan 1
Event2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Boston, United States
Duration: 2018 Jul 82018 Jul 13

Publication series

Name2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings

Conference

Conference2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018
CountryUnited States
CityBoston
Period18-07-0818-07-13

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Instrumentation
  • Radiation

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