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박영빈

Park, Young-Bin
Functional Intelligent Materials Lab.
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Self-powered triboelectric sensor based on a carbon fiber/glass fiber/epoxy structural composite for efficient traffic monitoring

Author(s)
Lee, SeonghwanPark, Young-Bin
Issued Date
2024-09
DOI
10.1016/j.nanoen.2024.109818
URI
https://scholarworks.unist.ac.kr/handle/201301/83304
Citation
NANO ENERGY, v.128, pp.109818
Abstract
Intelligent transportation systems (ITSs) are being investigated as potential solutions for traffic congestion. Triboelectric sensors (TESs) have gained prominence among ITS technologies owing to their efficiency and selfpowered capabilities in detecting external changes through friction-generated electrical signals. Herein, a traffic monitoring system using a fiber-reinforced plastic-based TES (FRP-TES) is proposed, designed with high-strength and high-stiffness fiber-reinforced plastic (FRP) as the core material. FRP is a structural composite comprising high-strength fibers impregnated with engineering resin. When the surface of the epoxy, which has a charged layer, reacts with the charged tire, electrostatic induction occurs in the carbon fibers. By leveraging the principles of carbon and glass fiber/epoxy-reinforced infrastructure, along with corresponding electrical properties, we analyze electrical signals produced when a tire traverses the FRP-TES. We subject the FRP-TES to electrical durability and tensile tests to verify signal stability and mechanical properties (strength <= 1770.87 MPa, modulus <= 41.38 GPa). The analysis proposes an effective method for obtaining the tire position, movement direction, speed, and acceleration using paired FRP-TES units. The proposed approach achieves significant reduction in maximum errors (0.52 % in speed, 3.24 % in acceleration) with eight evenly spaced FRP-TES units in a 240 mm section. A larger FRP-TES is fabricated to demonstrate practicality for personal mobility. Incorporating FRP-TES units into road infrastructure can enhance structural stability while providing reliable real -time data for traffic monitoring, accident response, and prediction.
Publisher
ELSEVIER
ISSN
2211-2855
Keyword (Author)
Self-powered systemsTriboelectric sensorsStructural compositesFiber reinforced plasticsTraffic monitoring
Keyword
NANOGENERATORFATIGUESYSTEM

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