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Optimal dynamic recharge scheduling for two stage wireless power transfer

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Title: Optimal dynamic recharge scheduling for two stage wireless power transfer
Authors: Pandiyan, A
Boyle, D
Kiziroglou, M
Wright, S
Yeatman, E
Item Type: Journal Article
Abstract: Many Industrial Internet of Things applications require autonomous operation and incorporate devices in inaccessible locations. Recent advances in wireless power transfer (WPT) and autonomous vehicle technologies, in combination, have the potential to solve a number of residual problems concerning the maintenance of, and data collection from embedded devices. Equipping inexpensive unmanned aerial vehicles (UAV) and embedded devices with subsystems to facilitate WPT allows a UAV to become a viable mobile power delivery vehicle (PDV) and data collection agent. A key challenge is therefore to ensure that a PDV can optimally schedule power delivery across the network, such that it is as reliable and resource efficient as possible. To achieve this and out-perform naive on-demand recharging strategies, we propose a two-stage wireless power network (WPN) approach in which a large network of devices may be grouped into small clusters, where packets of energy inductively delivered to each cluster by the PDV are acoustically distributed to devices within the cluster. We describe a novel dynamic recharge scheduling algorithm that combines genetic weighted clustering with nearest neighbour search to jointly minimize PDV travel distance and WPT losses. The efficacy and performance of the algorithm are evaluated in simulation using experimentally derived traces, and the algorithm is shown to achieve 90% throughput for large, dense networks.
Issue Date: 3-Nov-2020
Date of Acceptance: 22-Oct-2020
URI: http://hdl.handle.net/10044/1/84644
DOI: 10.1109/tii.2020.3035645
ISSN: 1551-3203
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Start Page: 5719
End Page: 5729
Journal / Book Title: IEEE Transactions on Industrial Informatics
Volume: 17
Issue: 8
Copyright Statement: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Commission of the European Communities
Natural Environment Research Council (NERC)
Funder's Grant Number: 722496
Keywords: 08 Information and Computing Sciences
09 Engineering
10 Technology
Electrical & Electronic Engineering
Publication Status: Published
Online Publication Date: 2020-11-03
Appears in Collections:Electrical and Electronic Engineering
Faculty of Natural Sciences
Faculty of Engineering