Two Degrees of Freedom in Two Directions Structure Triboelectric Nanogenerator for Vibration Energy Harvesting and Self-Powered Sensing

纳米发生器 摩擦电效应 振动 能量收集 电压 声学 机械能 能量(信号处理) 电气工程 功率(物理) 工程类 材料科学 物理 量子力学 复合材料
作者
Xinhua Wang,Gefan Yin,Tao Sun,Xiangjie Xu,Ghulam Rasool,Kamil Abbas
出处
期刊:ACS applied electronic materials [American Chemical Society]
卷期号:5 (12): 6500-6513 被引量:4
标识
DOI:10.1021/acsaelm.3c00897
摘要

The widely distributed reciprocating compressors contain abundant vibrational energy, and it is valuable to effectively harvest the mechanical vibration energy. However, the traditional vibration energy harvesters have shortages of a single harvesting direction and insufficient output under weak vibration excitation. Here, a two degrees of freedom in two directions structure triboelectric nanogenerator (TFTD-TENG) was proposed. TFTD-TENG can efficiently harvest the vertical and horizontal or composite directions vibration energy, and the additional solar cell (SC) on the TFTD-TENG can harvest static solar energy. To clarify its working principle, the kinematic characteristics and the mechanical models of the TFTD-TENG in horizontal and vertical directions were analyzed. Moreover, the main structural parameters were optimized. The vertical and horizontal output performance of the TFTD-TENG at vibration frequencies of 1–25 Hz and vibration amplitudes of 1–3 mm were comprehensively tested. For the composite vibration direction, a vibration direction recognition method based on the output voltage ratio was proposed. When the TFTD-TENG was installed on an air compressor, the output voltage of the vertical TENG was 192 V and the short-circuit current (Isc) was 8 μA, the output voltage of the horizontal TENG was 83 V and the Isc was 5 μA. And when the TENG units in two directions output in parallel, the TFTD-TENG can generate a maximum power of 1361.25 μW, matching a resistance value of 20 MΩ. The proposed TFTD-TENG shows excellent performance in vibration energy harvesting and self-powered sensing, which has great prospects in smart factories and artificial intelligence of things.
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