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Low power wireless technologies for AC current sensing

Ullah, Irfan (2021) Low power wireless technologies for AC current sensing. Doctor of Philosophy (PhD) thesis, University of Kent,. (doi:10.22024/UniKent/01.02.87042) (KAR id:87042)

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This thesis is concerned with the development of a novel RFID ac current sensing technique for smart power monitoring systems. The research aims to explore designing self-tuning RFID tags and antenna designs and transforming simple tags into passive ac current sensors.The sensing mechanism by which a self-tuning RFID tag is linked with a varactor tuning circuit and integrated into a current transformer is described. The proposed sensing tag structure is less complex and provides a cost-effective solution for power monitoring when many tags on individual appliances communicate wirelessly with a centrally mounted single RFID reader in the views of the tags to be read.New optimised RFID tag antenna designs for a current transformer are introduced. Antenna miniaturisation techniques are adopted in designing tag antennas to achieve compact physical integration with the transformer housing while maintaining the tag link. These optimisedtag antennas are designed in order to reduce the size of the tag system.The proposed current sensing concept is further explored to utilise two tag antennas in a single design. The two tag antennas are coupled with different tuning circuits and integrated into a single transformer for increasing the current sensing range of the sensor. The antenna design techniques of designing two tag antennas in close proximity with each other and how the mutual coupling between the tag antennas can be reduced are also studied.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Batchelor, John
Thesis advisor: Izquierdo, Benito Sanz
DOI/Identification number: 10.22024/UniKent/01.02.87042
Uncontrolled keywords: Self-tuning RFID tags, RFID sensing, ac current antenna sensors, wireless sensors, Internet of Things, smart home application, industry 4.0.
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
SWORD Depositor: System Moodle
Depositing User: System Moodle
Date Deposited: 10 Mar 2021 14:10 UTC
Last Modified: 19 May 2021 15:31 UTC
Resource URI: (The current URI for this page, for reference purposes)
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