Safe Charging for Wireless Power Transfer

Haipeng Dai; Yunhuai Liu; Guihai Chen; Xiaobing Wu; Tian He; Alex X. Liu; Huizhen Ma

doi:10.1109/TNET.2017.2750323

Safe Charging for Wireless Power Transfer

Haipeng Dai, Yunhuai Liu, Guihai Chen, Xiaobing Wu, Tian He, Alex X. Liu, Huizhen Ma

Center for Transportation Studies

Research output: Contribution to journal › Article › peer-review

89 Scopus citations

Abstract

As battery-powered mobile devices become more popular and energy hungry, wireless power transfer technology, which allows the power to be transferred from a charger to ambient devices wirelessly, receives intensive interests. Existing schemes mainly focus on the power transfer efficiency but overlook the health impairments caused by RF exposure. In this paper, we study the safe charging problem SCP of scheduling power chargers so that more energy can be received while no location in the field has electromagnetic radiation EMR exceeding a given threshold R_t. We show that SCP is NP-hard and propose a solution, which provably outperforms the optimal solution to SCP with a relaxed EMR threshold 1-ϵR_t. Testbed results based on 8 Powercast TX91501 chargers validate our results. Extensive simulation results show that the gap between our solution and the optimal one is only 6.7 whenϵ = 0.1, while a naive greedy algorithm is 34.6 below our solution.

Original language	English (US)
Pages (from-to)	3531-3544
Number of pages	14
Journal	IEEE/ACM Transactions on Networking
Volume	25
Issue number	6
DOIs	https://doi.org/10.1109/TNET.2017.2750323
State	Published - Dec 2017

Bibliographical note

Funding Information:
Manuscript received October 24, 2016; revised May 31, 2017; accepted August 18, 2017; approved by IEEE/ACM TRANSACTIONS on NETWORKING Editor C. Joo. Date of publication September 26, 2017; date of current version December 15, 2017. This work was supported in part by China 973 projects under Grant 2014CB340303, in part by the National Natural Science Foundation of China under Grant 61502229, Grant 61672353, Grant 61472252, Grant 61321491, Grant 61332018, Grant 61772046, Grant 61629302, Grant 61373130, Grant 61672276, and Grant 61472184, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20141319, in part by the National Science Foundation under Grant CNS-1318563, Grant CNS-1524698, and Grant CNS-1421407, in part by IIP-1632051, and in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program. (Corresponding authors: Yunhuai Liu; Guihai Chen; Tian He.) H. Dai, G. Chen, and H. Ma are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: haipengdai@nju.edu.cn; gchen@nju.edu.cn; mg1533037@smail.nju.edu.cn).

Publisher Copyright:
© 2017 IEEE.

Keywords

Electromagnetic radiation
optimization
wireless power transfer

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10.1109/TNET.2017.2750323

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@article{11a429dc1a904756aac790cfe3622805,

title = "Safe Charging for Wireless Power Transfer",

abstract = "As battery-powered mobile devices become more popular and energy hungry, wireless power transfer technology, which allows the power to be transferred from a charger to ambient devices wirelessly, receives intensive interests. Existing schemes mainly focus on the power transfer efficiency but overlook the health impairments caused by RF exposure. In this paper, we study the safe charging problem SCP of scheduling power chargers so that more energy can be received while no location in the field has electromagnetic radiation EMR exceeding a given threshold Rt. We show that SCP is NP-hard and propose a solution, which provably outperforms the optimal solution to SCP with a relaxed EMR threshold 1-ϵRt. Testbed results based on 8 Powercast TX91501 chargers validate our results. Extensive simulation results show that the gap between our solution and the optimal one is only 6.7 whenϵ = 0.1, while a naive greedy algorithm is 34.6 below our solution.",

keywords = "Electromagnetic radiation, optimization, wireless power transfer",

author = "Haipeng Dai and Yunhuai Liu and Guihai Chen and Xiaobing Wu and Tian He and Liu, {Alex X.} and Huizhen Ma",

note = "Funding Information: Manuscript received October 24, 2016; revised May 31, 2017; accepted August 18, 2017; approved by IEEE/ACM TRANSACTIONS on NETWORKING Editor C. Joo. Date of publication September 26, 2017; date of current version December 15, 2017. This work was supported in part by China 973 projects under Grant 2014CB340303, in part by the National Natural Science Foundation of China under Grant 61502229, Grant 61672353, Grant 61472252, Grant 61321491, Grant 61332018, Grant 61772046, Grant 61629302, Grant 61373130, Grant 61672276, and Grant 61472184, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20141319, in part by the National Science Foundation under Grant CNS-1318563, Grant CNS-1524698, and Grant CNS-1421407, in part by IIP-1632051, and in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program. (Corresponding authors: Yunhuai Liu; Guihai Chen; Tian He.) H. Dai, G. Chen, and H. Ma are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: haipengdai@nju.edu.cn; gchen@nju.edu.cn; mg1533037@smail.nju.edu.cn). Publisher Copyright: {\textcopyright} 2017 IEEE.",

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AU - Liu, Alex X.

AU - Ma, Huizhen

N1 - Funding Information: Manuscript received October 24, 2016; revised May 31, 2017; accepted August 18, 2017; approved by IEEE/ACM TRANSACTIONS on NETWORKING Editor C. Joo. Date of publication September 26, 2017; date of current version December 15, 2017. This work was supported in part by China 973 projects under Grant 2014CB340303, in part by the National Natural Science Foundation of China under Grant 61502229, Grant 61672353, Grant 61472252, Grant 61321491, Grant 61332018, Grant 61772046, Grant 61629302, Grant 61373130, Grant 61672276, and Grant 61472184, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20141319, in part by the National Science Foundation under Grant CNS-1318563, Grant CNS-1524698, and Grant CNS-1421407, in part by IIP-1632051, and in part by the Jiangsu High-level Innovation and Entrepreneurship (Shuangchuang) Program. (Corresponding authors: Yunhuai Liu; Guihai Chen; Tian He.) H. Dai, G. Chen, and H. Ma are with the State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210023, China (e-mail: haipengdai@nju.edu.cn; gchen@nju.edu.cn; mg1533037@smail.nju.edu.cn). Publisher Copyright: © 2017 IEEE.

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N2 - As battery-powered mobile devices become more popular and energy hungry, wireless power transfer technology, which allows the power to be transferred from a charger to ambient devices wirelessly, receives intensive interests. Existing schemes mainly focus on the power transfer efficiency but overlook the health impairments caused by RF exposure. In this paper, we study the safe charging problem SCP of scheduling power chargers so that more energy can be received while no location in the field has electromagnetic radiation EMR exceeding a given threshold Rt. We show that SCP is NP-hard and propose a solution, which provably outperforms the optimal solution to SCP with a relaxed EMR threshold 1-ϵRt. Testbed results based on 8 Powercast TX91501 chargers validate our results. Extensive simulation results show that the gap between our solution and the optimal one is only 6.7 whenϵ = 0.1, while a naive greedy algorithm is 34.6 below our solution.

AB - As battery-powered mobile devices become more popular and energy hungry, wireless power transfer technology, which allows the power to be transferred from a charger to ambient devices wirelessly, receives intensive interests. Existing schemes mainly focus on the power transfer efficiency but overlook the health impairments caused by RF exposure. In this paper, we study the safe charging problem SCP of scheduling power chargers so that more energy can be received while no location in the field has electromagnetic radiation EMR exceeding a given threshold Rt. We show that SCP is NP-hard and propose a solution, which provably outperforms the optimal solution to SCP with a relaxed EMR threshold 1-ϵRt. Testbed results based on 8 Powercast TX91501 chargers validate our results. Extensive simulation results show that the gap between our solution and the optimal one is only 6.7 whenϵ = 0.1, while a naive greedy algorithm is 34.6 below our solution.

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KW - optimization

KW - wireless power transfer

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Safe Charging for Wireless Power Transfer

Abstract

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