A Natural Gradient Biological-Enabled Multimodal Triboelectric Nanogenerator for Driving Safety Monitoring

Abstract

A key element to ensuring driving safety is to provide a sufficient braking distance. Inspired by the nature triply periodic minimal surface (TPMS), a gradient and multimodal triboelectric nanogenerator (GM-TENG) is proposed with high sensitivity and excellent multimodal monitoring. The gradient TPMS structure exhibits the multi-stage stress-strain properties of typical porous metamaterials. Significantly, the multimodal monitoring capability depends on the implicit function of the defined level constant <i>c</i>, which directly contributes to the multimodal driving safety monitoring. The mechanical and electrical responsive behavior of the GM-TENG is analyzed to identify the applied speed, load, and working mode. In addition, optimized peak open-circuit voltage (<i>V</i>_oc) is demonstrated for self-awareness of the braking condition. The braking distance factor (<i>L</i>) is conceived to construct the self-aware equation of the friction coefficient based on the integration of <i>V</i>_oc with respect to time. Importantly, <i>R</i>-squared up to 94.29 % can be obtained, which improves self-aware accuracy and real-time capabilities. This natural structure and self-aware device provide an effective strategy to improve driving safety, which contributes to the improvement of road safety and presents self-powered sensing with potential applications in an intelligent transportation system.