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

Chin Lung Yang; Shao Ping Cheng; Chung En Yu

doi:10.1109/APUSNCURSINRSM.2018.8609008

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

Chin Lung Yang, Shao Ping Cheng, Chung En Yu

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2537-2538
Number of pages	2
ISBN (Electronic)	9781538671023
DOIs	https://doi.org/10.1109/APUSNCURSINRSM.2018.8609008
Publication status	Published - 2018 Jan 1
Event	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Boston, United States Duration: 2018 Jul 8 → 2018 Jul 13

Publication series

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

Conference

Conference	2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018
Country	United States
City	Boston
Period	18-07-08 → 18-07-13

All Science Journal Classification (ASJC) codes

Computer Networks and Communications
Instrumentation
Radiation

Access to Document

10.1109/APUSNCURSINRSM.2018.8609008

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Yang, C. L., Cheng, S. P., & Yu, C. E. (2018). Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms. In 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings (pp. 2537-2538). [8609008] (2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APUSNCURSINRSM.2018.8609008

Yang, Chin Lung ; Cheng, Shao Ping ; Yu, Chung En. / Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms. 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 2537-2538 (2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings).

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title = "Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms",

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.",

author = "Yang, {Chin Lung} and Cheng, {Shao Ping} and Yu, {Chung En}",

year = "2018",

month = jan,

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doi = "10.1109/APUSNCURSINRSM.2018.8609008",

language = "English",

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

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

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note = "2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 ; Conference date: 08-07-2018 Through 13-07-2018",

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Yang, CL, Cheng, SP & Yu, CE 2018, Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms. in 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings., 8609008, 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings, Institute of Electrical and Electronics Engineers Inc., pp. 2537-2538, 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018, Boston, United States, 18-07-08. https://doi.org/10.1109/APUSNCURSINRSM.2018.8609008

Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms. / Yang, Chin Lung; Cheng, Shao Ping; Yu, Chung En.

2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. p. 2537-2538 8609008 (2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - 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.

AB - 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.

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Yang CL, Cheng SP, Yu CE. Fused Helico-Spiral Coil Design Using Both Neural Network and Generic Algorithms. In 2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2018. p. 2537-2538. 8609008. (2018 IEEE Antennas and Propagation Society International Symposium and USNC/URSI National Radio Science Meeting, APSURSI 2018 - Proceedings). https://doi.org/10.1109/APUSNCURSINRSM.2018.8609008