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Design of a High-Efficiency DC-DC Boost Converter for RF Energy Harvesting IoT Sensorsoa mark
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Publication Year
2022-12-01
Publisher
MDPI
Citation
Sensors, Vol.22
Keyword
boost converterDC-DC converterefficiency optimizationhigh efficiencyRF energy harvesting
Mesh Keyword
BOOST converterDc - dc boost convertersEfficiency optimizationHigher efficiencyInput voltagesLoss modelMaximum powerPower conversion efficienciesRF energy harvestingWide input voltage ranges
All Science Classification Codes (ASJC)
Analytical ChemistryInformation SystemsBiochemistryAtomic and Molecular Physics, and OpticsInstrumentationElectrical and Electronic Engineering
Abstract
In this paper, an optimal design of a high-efficiency DC-DC boost converter is proposed for RF energy harvesting Internet of Things (IoT) sensors. Since the output DC voltage of the RF-DC rectifier for RF energy harvesting varies considerably depending on the RF input power, the DC-DC boost converter following the RF-DC rectifier is required to achieve high power conversion efficiency (PCE) in a wide input voltage range. Therefore, based on the loss analysis and modeling of an inductor-based DC-DC boost converter, an optimal design method of design parameters, including inductance and peak inductor current, is proposed to obtain the maximum PCE by minimizing the total loss according to different input voltages in a wide input voltage range. A high-efficiency DC-DC boost converter for RF energy harvesting applications is designed using a 65 nm CMOS process. The modeled total losses agree well with the circuit simulation results and the proposed loss modeling results accurately predict the optimal design parameters to obtain the maximum PCE. Based on the proposed loss modeling, the optimally designed DC-DC boost converter achieves a power conversion efficiency of 96.5% at a low input voltage of 0.1 V and a peak efficiency of 98.4% at an input voltage of 0.4 V.
ISSN
1424-8220
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/33148
DOI
https://doi.org/10.3390/s222410007
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Type
Article
Funding
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1A2C1010613).
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 Kwon, Ickjin Image
Kwon, Ickjin권익진
Department of Electrical and Computer Engineering
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