NDLI: Efficiency optimization of class-D biomedical inductive wireless power transfer systems by means of frequency adjustment

Content Provider	IEEE Xplore Digital Library
Author	Schormans, M. Valente, V. Demosthenous, A.
Copyright Year	2015
Description	Author affiliation: Dept. of Electron. & Electr. Eng., Univ. Coll. London, London, UK (Schormans, M.; Valente, V.; Demosthenous, A.)
Abstract	Inductive powering for implanted medical devices is a commonly employed technique, that allows for implants to avoid more dangerous methods such as the use of transcutaneous wires or implanted batteries. However, wireless powering in this way also comes with a number of difficulties and conflicting requirements, which are often met by using designs based on compromise. In particular, one aspect common to most inductive power links is that they are driven with a fixed frequency, which may not be optimal depending on factors such as coupling and load. In this paper, a method is proposed in which an inductive power link is driven by a frequency that is maintained at an optimum value $f_{opt}$ , to ensure that the link is in resonance. In order to maintain this resonance, a phase tracking technique is employed at the primary side of the link; this allows for compensation of changes in coil separation and load. The technique is shown to provide significant improvements in maintained secondary voltage and efficiency for a range of loads when the link is overcoupled.
Starting Page	5473
Ending Page	5476
File Size	2846894
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7319630
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Resonant frequency Couplings Implants Inductance Monitoring Mathematical model Optimized production technology
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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