Computational investigation of material combinations in triboelectric generators

The recent development of internet of things (IoT) and sensor networks dramatically increased the demand for robust energy harvesting techniques for sensors to work in self-powered mode. Scavenging mechanical energy from ambient environment through friction and vibration has attracted great attention. Among electromagnetic, electrostatic, piezoelectric and triboelectric mechanical energy harvesting technologies, triboelectric generators (TEGs) based on coupling of contact electrification and electrostatic induction, shows a promising technology owing to their numerous advantages: high output power, high energy conversion efficiency and low cost materials and fabrication. This paper focuses on the computational study of sliding mode of TEG with different triboelectric material pairs using Comsol Multiphysics. The output characteristics of the TEG are evaluated with respect to the material properties. The effect of material selection is investigated in the selected TEG sliding model in terms of voltage with respect to the sliding distance.