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Ultra-Compact Pulse Charger for Lithium Polymer Battery with Simple Built-in Resistance Compensation in Biomedical Applications

Authors
Kim, YeminLee, JunhyuckLee, Byunghun
Issue Date
Aug-2024
Publisher
Institute of Electrical and Electronics Engineers
Keywords
Battery charger; biomedical applications; built-in resistance (BIR); active implantable medical devices (AIMDs); lithium plating phenomenon; lithium polymer battery; pulse charging; wireless power transfer (WPT)
Citation
IEEE Transactions on Biomedical Circuits and Systems, v.18, no.4, pp 746 - 755
Pages
10
Indexed
SCIE
SCOPUS
Journal Title
IEEE Transactions on Biomedical Circuits and Systems
Volume
18
Number
4
Start Page
746
End Page
755
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/210183
DOI
10.1109/TBCAS.2024.3401846
ISSN
1932-4545
1940-9990
Abstract
Active implantable medical devices (AIMDs) rely on batteries for uninterrupted operation and patient safety. Therefore, it is critical to ensure battery safety and longevity. To achieve this, constant current/constant voltage (CC/CV) methods have been commonly used and research has been conducted to compensate for the effects of built-in resistance (BIR) of batteries. However, conventional CC/CV methods may pose the risk of lithium plating. Furthermore, conventional compensation methods for BIR require external components, complex algorithms, or large chip sizes, which inhibit the miniaturization and integration of AIMDs. To address this issue, we have developed a pulse charger that utilizes pulse current to ensure battery safety and facilitate easy compensation for BIR. A comparison with previous research on BIR compensation shows that our approach achieves the smallest chip size of 0.0062 mm2 and the lowest system complexity using 1-bit ADC. In addition, we have demonstrated a reduction in charging time by at least 44.4% compared to conventional CC/CV methods, validating the effectiveness of our system’s BIR compensation. The compact size and safety features of the proposed charging system make it promising for AIMDs, which have space-constrained environments.
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