Energy science is becoming an increasingly important multi-disciplinary area, for not only addressing the worldwide energy crisis, but also realizing desired power sources with advanced features for portable electronic devices and sensor networks. Very recently, based on triboelectric effect and electrostatic induction, a fundamentally new technology, triboelectric nanogenerator, has been demonstrated which shows unique merits. But so far, the main limitation for continuing optimizing their output performance is a lack of fundamental understanding of their core working mechanism. In this thesis research, we first unveil the fundamental theory and output characteristics of triboelectric nanogenerators. Then, we apply the developed theory to the TENG-based self-powered system design. We have developed the first genuine self-powered system to meet mW requirement of personal electronics. The system includes a multilayered TENG, a power management circuit with 60% total efficiency, and a low leakage energy storage device. Our power management circuit provides the total efficiency that is about two magnitudes higher than the traditional direct charging. And the total system performance is 330 times higher than the state-of-art designs. Driven by palm tapping, this power unit can provide a continuous DC electricity of 1.044 mW on average power in a regulated and managed manner that can be universally applied as a standard power source for continuously driving numerous conventional electronics, such as a thermometer, a heart rate monitor (electrocardiograph/ECG system), a pedometer, a wearable electronic watch, a scientific calculator, and a wireless radio-frequency communication system. Our study demonstrates the first power unit that utilizes widely accessible biomechanical energy source to sustainably drive a broad range of commercial mobile and wearable electronic devices. This self-charging unit is a paradigm shift towards infinite-lifetime energy sources that can never be achieved solely by batteries.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54954 |
Date | 27 May 2016 |
Creators | Niu, Simiao |
Contributors | Wang, Zhong Lin |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Dissertation |
Format | application/pdf |
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