摩擦电效应
纳米发生器
材料科学
电容
电容器
静电感应
机械能
接触带电
电压
电气工程
电容感应
整流器(神经网络)
能量收集
功率(物理)
电极
物理
工程类
计算机科学
随机神经网络
机器学习
循环神经网络
复合材料
量子力学
人工神经网络
作者
Simiao Niu,Zhong Lin Wang
出处
期刊:Nano Energy
[Elsevier]
日期:2014-11-21
卷期号:14: 161-192
被引量:1090
标识
DOI:10.1016/j.nanoen.2014.11.034
摘要
Triboelectric nanogenerator (TENG) technology based on contact electrification and electrostatic induction is an emerging new mechanical energy harvesting technology with numerous advantages. The current area power density of TENGs has reached 313 W/m2 and their volume energy density has reached 490 kW/m3. In this review, we systematically analyzed the theoretical system of triboelectric nanogenerators. Starting from the physics of TENGs, we thoroughly discussed their fundamental working principle and simulation method. Then the intrinsic output characteristics, load characteristics, and optimization strategy is in-depth discussed. TENGs have inherent capacitive behavior and their governing equation is their V–Q–x relationship. There are two capacitance formed between the tribo-charged dielectric surface and the two metal electrodes, respectively. The ratio of these two capacitances changes with the position of this dielectric surface, inducing electrons to transfer between the metal electrodes under short circuit conditions. This is the core working mechanism of triboelectric generators and different TENG fundamental modes can be classified based on the changing behavior of these two capacitances. Their first-order lumped-parameter equivalent circuit model is a voltage source in series with a capacitor. Their resistive load characteristics have a “three-working-region” behavior because of the impedance match mechanism. Besides, when TENGs are utilized to charge a capacitor with a bridge rectifier in multiple motion cycles, it is equivalent to utilizing a constant DC voltage source with an internal resistance to charge. The optimization techniques for all TENG fundamental modes are also discussed in detail. The theoretical system reviewed in this work provides a theoretical basis of TENGs and can be utilized as a guideline for TENG designers to continue improving TENG output performance.
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