基于折纸-摩擦纳米发电的路面抗滑性能自驱动感知

Self-Powered Pavement Skid-Resistance Sensing Based on Origami-Inspired Triboelectric Nanogenerator

摘要:

准确评估路面抗滑性能对改善行车安全、减少交通事故具有重要意义。当前的测试方法在复杂路况下无法迅速判断安全车速及跟车距离，容易引发交通事故。将摩擦纳米发电与折纸技术结合，基于吉村折纸构型开发摩擦纳米发电机 （YO-TENG），将其植入到轮胎内表面，构建YO-TENG支持的智能轮胎。基于全新搭建的室内智能轮胎测试平台评估多因素下（摩擦系数、车速）YO-TENG对路面抗滑性能实时感知的准确性。结果表明：YO-TENG的短路电流峰值与路面摩擦系数拟合系数达96.36 %。即使引入实际车速的影响，相关系数仍达90.64 %。该研究对路面抗滑性能的自驱动感知提供了理论指导。

Abstract:

The study of pavement skid resistance is of great significance for improving driving safety and reducing traffic accidents. However， existing vision-based onboard units cannot quickly determine safe speed and following distance in complex road conditions， contributing to traffic accidents. To address this challenge， this paper integrates the triboelectric nanogenerator （TENG） with origami design principles， leading to the development of a Yoshimura origami-inspired triboelectric nanogenerator （YO-TENG）. This YO-TENG is mounted onto the surface of vehicle tires， forming a YO-TENG smart tire system. Moreover， the accuracy of YO-TENG in real-time monitoring of pavement skid resistance under different conditions， specifically friction coefficient and vehicle speed， was evaluated using the newly built indoor intelligent tire testing platform. The results show that the fitting degree between the short-circuit current peak value of YO-TENG and the road friction coefficient is as high as approximately 96.36 %. Even when the influence of actual vehicle speed is considered， the correlation coefficient still reaches 90.64 %. This paper provides valuable theoretical guidance for the development of self-powered， real-time sensing systems for pavement skid resistance monitoring.