Physical intelligence-based working mode adaptable triboelectric nanogenerator for effective wind energy harvesting in broad range

Abstract

Triboelectric nanogenerators (TENGs) offer a promising solution for harvesting wind energy, which is a renewable source of natural energy that can be dissipated. However, designing a wind energy harvester presents a significant challenge due to the dynamic characteristics of ambient wind, including irregularity and broad wind speed ranges. In this work, we suggested a spontaneous working mode changeable TENG (SM-TENG) designed for effectively harvesting wind energy within a broad range of wind speeds ranging from a breeze of 2 m/s to a gale of 25 m/s. The SM-TENG consists of a physical intelligence-based rotator that can switch contact and separation mode depending on the input wind speed. Under a breeze, the SM-TENG can generate triboelectricity by fluttering a dielectric film based on vertical contact separation (F-TENG) due to intentional pressure imbalance. Meanwhile, when wind speed exceeds a certain wind speed of 5 m/s, the SM-TENG begins to harvest more wind by rotating the rotator based on the sliding contact separation (R-TENG), indicating that the SM-TENG can harvest wind by selecting the appropriate working mode. We adopted the Taguchi method to enhance performance by identifying the optimal parameters, affecting the desired output. In addition, the SM-TENG can successfully power a light-emitting diode display and a Bluetooth thermometer within a wide range of wind speeds. Therefore, this work may provide a strategy for designing a wind energy harvester capable of harvesting in a wide range of wind as well as 0could contribute to the feasibility of Internet of Things through distributed energy.