能量收集
整流器(神经网络)
摩擦电效应
电感器
电气工程
纳米发生器
电子线路
材料科学
振动
阻抗匹配
电阻抗
能量(信号处理)
电压
声学
物理
工程类
计算机科学
机器学习
随机神经网络
量子力学
循环神经网络
复合材料
人工神经网络
作者
Madhav Pathak,Ratnesh Kumar
摘要
One major challenge to the usability of IoT devices is limited onboard battery lifetime. Integrating an energy harvester to scavenge the energy from ambient sources is a viable green option. In recent 5 years, Triboelectric Nanogenerators (TENG) have gained attention for harvesting ambient vibration energy from sources ranging from ocean waves to human body motion due to their flexibility in the choice of materials and fabrication processes. However, due to the high nonlinearly varying impedance (typically in mega ohms) of TENG, standard full wave rectifier based AC to DC conversion for energy extraction is unable to provide a matching impedance needed for optimized energy transfer. In the presented work, Synchronous Charge Extraction (SCE), Parallel and Series synchronized switch harvesting on inductor (P-SSHI and S-SSHI) energy extraction circuits are mathematically modeled, analyzed, simulated, and compared with the standard full wave rectifier (FWR) circuit for the first time to the best of our knowledge. While the above-mentioned extraction schemes have been studied for piezoelectric transducers, the models (and gains) are different in the case of triboelectric transducers. For TENG with an area, 12 x 8 cm2, surface charge density 8 μC=m2, and subjected to vibration with 3 mm amplitude and 1 Hz frequency, energy gains of 2.8, 14.5, 385 over FWR were realized for P-SSHI, S-SSHI and SCE for a 5V battery load respectively. The above findings were also confirmed by SPICE-based circuit simulation.
科研通智能强力驱动
Strongly Powered by AbleSci AI