Journal Home > Volume 9 , Issue 2

Effective optimization methods are used to guide the optimal design of coil parameters, which is significant for improving the transmission performance of the wireless power transfer (WPT) system. Traditional methods mostly rely on the exhaustive attack method and finite element analysis (FEA) to achieve the coil parameter design, which have the disadvantages of complex modeling and time-consumption. To overcome these limitations, this study proposes an optimization strategy based on the genetic algorithm (GA), which considers the actual requirements of the efficiency and power of the WPT system. First, a direct integration method is proposed to simplify the analytical solution process of the mutual inductance between the hexagonal coils. Based on the mutual inductance model, the transmission characteristics of the hexagonal coil WPT system are deeply analyzed by the control variable method. Most importantly, with the proposed optimization objective function and its constraints, the GA is used to automatically achieve multi-parameter optimization of the hexagonal coil. Finally, a 500 W WPT system experimental platform is established, and the experimental results verify the feasibility of the proposed optimization method.


menu
Abstract
Full text
Outline
About this article

Optimal Design of Transmission Characteristics for Hexagonal Coil Wireless Power Transfer System Based on Genetic Algorithm

Show Author's information Ping’an Tan1( )Bin Song1Xu Shangguan1Huadong Liu2
School of Automation and Electronic Information, Xiangtan University, Xiangtan 411105, China
CRRC Zhuzhou Electric Locomotive Research Institute Co., Ltd., Zhuzhou 412001, China

Abstract

Effective optimization methods are used to guide the optimal design of coil parameters, which is significant for improving the transmission performance of the wireless power transfer (WPT) system. Traditional methods mostly rely on the exhaustive attack method and finite element analysis (FEA) to achieve the coil parameter design, which have the disadvantages of complex modeling and time-consumption. To overcome these limitations, this study proposes an optimization strategy based on the genetic algorithm (GA), which considers the actual requirements of the efficiency and power of the WPT system. First, a direct integration method is proposed to simplify the analytical solution process of the mutual inductance between the hexagonal coils. Based on the mutual inductance model, the transmission characteristics of the hexagonal coil WPT system are deeply analyzed by the control variable method. Most importantly, with the proposed optimization objective function and its constraints, the GA is used to automatically achieve multi-parameter optimization of the hexagonal coil. Finally, a 500 W WPT system experimental platform is established, and the experimental results verify the feasibility of the proposed optimization method.

Keywords: Wireless power transfer (WPT), genetic algorithm (GA), optimal design, hexagonal coil, misalignment

References(23)

[1]

B Kallel, O Kanoun, H Trabelsi. Large air gap misalignment tolerable multi-coil inductive power transfer for wireless sensors. IET Power Electronics, 2016, 9(8): 1768-1774.

[2]

J Sampath, A Alphones, D M Vilathgamuwa. Figure of merit for the optimization of wireless power transfer system against misalignment tolerance. IEEE Transactions on Power Electronics, 2017, 32(6): 4359-4369.

[3]

Y Yang, J Cui, X Cui. Design and analysis of magnetic coils for optimizing the coupling coefficient in an electric vehicle wireless power transfer system. Energies, 2020, 13(16): 4143.

[4]

K Song, G Yang, Y Guo, et al. Design of DD coil with high misalignment tolerance and low EMF emissions for wireless electric vehicle charging system. IEEE Transactions on Power Electronics, 2020, 35(9): 9034-9045.

[5]
T Noda, T Nagashima, H Sekiya. A design of inductively coupled wireless power transfer system with coupling coil optimization. 2015 IEEE International Telecommunications Energy Conference (INTELEC), 18-22 October, 2015, Osaka, Japan. IEEE, 2016: 1-6.
DOI
[6]

Z Zhao, Z Yang, F Lin, et al. Coil optimization of wireless power transfer system applied in trams based on parking wrror law. Proceedings of the CSEE, 2017, 37: 196-203.

[7]
Y Fang, M Pong. A Bayesian optimization and partial element equivalent circuit approach to coil design in inductive power transfer systems. 2018 IEEE PELS Workshop on Emerging Technologies: Wireless Power Transfer (WoW), 03-07 June, 2018, Montreal, QC, Canada. IEEE, 2018: 3-7.
DOI
[8]

R J Liu, J Wang, J Y Shen. An optimal design of resonant coils for wireless power transfer system based on improved artificial bee colony algorithm. Applied Mechanics & Materials, 2014, 614: 168-171.

[9]

P Tan, T Peng, X Gao, et al. Flexible combination and switching control for robust wireless power transfer system with hexagonal array coil. IEEE Transactions on Power Electronics, 2021, 36(4): 3868-3882.

[10]

W Chen, C Liu, C H T Lee, et al. Cost-effectiveness comparison of coupler designs of wireless power transfer for electric vehicle dynamic charging. Energies, 2016, 9(11): 906.

[11]

I U Castillo-Zamora, P S Huynh, D Vincent, et al. Hexagonal geometry coil for a WPT high-power fast charging application. IEEE Transactions on Transportation Electrification, 2019, 5(4): 946-956.

[12]

Y Wang, F Lin, Z Yang, et al. Analysis of the influence of compensation capacitance errors of a wireless power transfer system with SS topology. Energies, 2017, 10(12): 2177.

[13]
P Qi, J Xu, F Yi, et al. The characteristic analysis of magnetically coupled resonant wireless power transmission based on SS compensation structure. 2017 First International Conference on Electronics Instrumentation & Information Systems (EⅡS), 03-05 June, 2017, Harbin, China. IEEE, 2017: 1-4.
DOI
[14]
L Yang, J Fan, T Zuo, et al. Simulation study on series model of wireless power transfer via magnetic resonance coupling. 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC), 03-05 October, 2017, Chongqing, China. IEEE, 2017: 191-195.
[15]

K Andre, K Aresteidis, M Robert, et al. Wireless power transfer via strongly coupled magnetic resonances. Science, 2007, 317(5834): 83-86.

[16]

T Mizuno, S Enoki, T Asahina, et al. Reduction of proximity effect in coil using magnetoplated wire. IEEE Transactions on Magnetics, 2007, 43(6): 2654-2656.

[17]

T Mizuno, S Yachi, A Kamiya, et al. Improvement in efficiency of wireless power transfer of magnetic resonant coupling using magnetoplated wire. IEEE Transactions on Magnetics, 2011, 47(10): 4445-4448.

[18]

H Tavakkoli, E Abbaspour-Sani, A Khalilzadegan, et al. Analytical study of mutual inductance of hexagonal and octagonal spiral planer coils. Sensors and Actuators A Physical, 2016, 247: 53-64.

[19]

X Mou, O Groling, H Sun. Energy efficient and adaptive design for wireless power transfer in electric vehicles. IEEE Transactions on Industrial Electronics, 2017, 64(9): 7250-7260.

[20]

X Wang, Y Wang, Y Liang, et al. Study on the transmission characteristics of magnetic resonance wireless power transfer system. International Journal of Microwave and Wireless Technologies, 2017, 9(9): 1-9.

[21]
P Tan, Y Fu, C Liu, et al. Modeling of mutual inductance for hexagonal coils with horizontal misalignment in wireless power transfer. 2018 IEEE Energy Conversion Congress and Exposition (ECCE), 23-27 September, 2018, Portland, OR, USA. IEEE, 2018: 1981-1986.
DOI
[22]

J S Jin, S Jung, J K Han. Development of wireless power transmission system for transfer cart with shortened track. Applied Sciences, 2020, 10(14): 4694.

[23]
O Trachtenberg, A Shoihet, E Beer, et al. Quadrature demodulator based output voltage and load estimation of a resonant inductive WPT link. 2019 IEEE PELS Workshop on Emerging Technologies: Wireless Power Transfer (WoW), 18-21 June, 2019, London, UK. IEEE, 2019: 81-84.
DOI
Publication history
Copyright

Publication history

Received: 29 January 2022
Revised: 09 May 2022
Accepted: 04 August 2022
Published: 17 April 2023
Issue date: June 2023

Copyright

© 2023 China Machinery Industry Information Institute
Return