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  5. Rotating-Disk-Based Hybridized Electromagnetic–Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors

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Article
en
2016

Rotating-Disk-Based Hybridized Electromagnetic–Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors

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en
2016
Vol 10 (6)
Vol. 10
DOI: 10.1021/acsnano.6b02384

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Zhong Lin Wang
Zhong Lin Wang

Beijing Institute of Technology

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Binbin Zhang
Jun Chen
Long Jin
+6 more

Abstract

Wireless traffic volume detectors play a critical role for measuring the traffic-flow in a real-time for current Intelligent Traffic System. However, as a battery-operated electronic device, regularly replacing battery remains a great challenge, especially in the remote area and wide distribution. Here, we report a self-powered active wireless traffic volume sensor by using a rotating-disk-based hybridized nanogenerator of triboelectric nanogenerator and electromagnetic generator as the sustainable power source. Operated at a rotating rate of 1000 rpm, the device delivered an output power of 17.5 mW, corresponding to a volume power density of 55.7 W/m(3) (Pd = P/V, see Supporting Information for detailed calculation) at a loading resistance of 700 Ω. The hybridized nanogenerator was demonstrated to effectively harvest energy from wind generated by a moving vehicle through the tunnel. And the delivered power is capable of triggering a counter via a wireless transmitter for real-time monitoring the traffic volume in the tunnel. This study further expands the applications of triboelectric nanogenerators for high-performance ambient mechanical energy harvesting and as sustainable power sources for driving wireless traffic volume sensors.

How to cite this publication

Binbin Zhang, Jun Chen, Long Jin, Weili Deng, Lei Zhang, Haitao Zhang, Minhao Zhu, Weiqing Yang, Zhong Lin Wang (2016). Rotating-Disk-Based Hybridized Electromagnetic–Triboelectric Nanogenerator for Sustainably Powering Wireless Traffic Volume Sensors. , 10(6), DOI: https://doi.org/10.1021/acsnano.6b02384.

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Publication Details

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Article

Year

2016

Authors

9

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0

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0

Language

en

DOI

https://doi.org/10.1021/acsnano.6b02384

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