A 180 nA Quiescent Current Digital Control Dual-Mode Buck Converter With a Pulse-Skipping Load Detector for Long-Range Applications
Author:
Affiliation:
1. Industry Academy Innovation School, National Yang Ming Chiao Tung University, Hsinchu City, Taiwan
2. Electrical Engineering Department, National Chung Cheng University, Chiayi, Taiwan
Funder
Ministry of Science and Technology, Taiwan
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Hardware and Architecture
Link
http://xplorestaging.ieee.org/ielx7/8919/10164683/10115224.pdf?arnumber=10115224
Reference22 articles.
1. A Design of a 92.4% Efficiency Triple Mode Control DC–DC Buck Converter With Low Power Retention Mode and Adaptive Zero Current Detector for IoT/Wearable Applications
2. A 50 nW-to-10 mW output power tri-mode digital buck converter with self-tracking zero current detection for photovoltaic energy harvesting;chen;IEEE J Solid-State Circuits,2016
3. A Digital-Control Buck Converter with Dual Pulse-Skipping Modes for Internet of Things
4. An Ultra-Low Quiescent Current Tri-Mode DC-DC Buck Converter With 92.1% Peak Efficiency for IoT Applications
5. A 470-nA Quiescent Current and 92.7%/94.7% Efficiency DCT/PWM Control Buck Converter With Seamless Mode Selection for IoT Application
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1. A 60-nA IQ 96.5% Peak Efficiency Buck Converter with Wide Load Range for Internet of Things;2024 IEEE International Symposium on Circuits and Systems (ISCAS);2024-05-19
2. Buck Converter With Load Adaptive Losses and 256x Sub-mW Load Transient Response Time of 0.8 ms Using Synchronous Control;IEEE Transactions on Power Electronics;2024-05
3. A 55nA Quiescent Current Power-Wise Buck Converter With 1$\upmu$A–600mA Load Range and 0.5V–1.8V Flexible Output Voltage Options;IEEE Transactions on Circuits and Systems I: Regular Papers;2024
4. Implementation of Adaptive Pulse Skipping Modulation based Quadratic Buck Converter for Light Load Applications;2023 11th National Power Electronics Conference (NPEC);2023-12-14
5. SG-Grasp: Semantic Segmentation Guided Robotic Grasp Oriented to Weakly Textured Objects Based on Visual Perception Sensors;IEEE Sensors Journal;2023-11-15
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