Indirect diagnosis methods of energy storage capability for mobile devices with USB power delivery

Abstract

Autonomous distributed power grids have attracted attention as a way to utilize renewable energy to achieve a carbon-neutral society. In order to properly operate these grids, it is necessary to obtain sufficient information on the supply and demand power capabilities and battery health of connected devices in a short time. In addition, methods based on direct current are essential to maximizing the use of renewable energy. This study proposes a method for acquiring information about the energy storage of devices connected to the grid via USB power delivery using deep learning techniques. Furthermore, we propose a method to diagnose the embedded battery health of the device based on short-time monitoring.