整流器(神经网络)
电压
能量收集
模式(计算机接口)
压电
偏压
能量(信号处理)
精密整流器
电气工程
材料科学
电子工程
工程类
计算机科学
物理
功率因数
随机神经网络
操作系统
量子力学
机器学习
循环神经网络
人工神经网络
标识
DOI:10.1109/tpel.2025.3532856
摘要
Various bias-flip rectifiers were proposed to improve the energy extraction performance for piezoelectric energy harvesting (PEH), which requires a power supply. However, no stable power supply is available when the system starts from a cold state. Typically, during the cold state, the system operates as a passive full bridge rectifier (FBR) to build up a stable power supply by charging a capacitor and then switching to the active rectifier after the cold state. Unfortunately, the system cannot start up if the open circuit voltage from a piezoelectric transducer (PT) is lower than the required supply voltage level. As a result, the system would end up with cold startup failure. This article proposes a two-mode bias-flip rectifier, which addresses the startup issue by lowering the required input open circuit voltage from the PT. The proposed design was fabricated in a 180-nm BCD process. Measurement results show that the necessary open-circuit voltage from the PT is lowered by 73% to achieve a successful cold startup, and the proposed system achieves 1182% energy extraction enhancement compared to a passive FBR.
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