Energy Management of a HUB System for Charging Batteries of Light Vehicles

Due to the increase in shared light and heavy electric vehicles, the use of charging centers for battery swapping is booming. In the process of battery charging management, it is essential to have a tool that allows predicting the number of batteries to be charged, which facilitates charge management and thus reduces energy costs. This paper presents the development of an algorithm based on Machine Learning that allows anticipating the number of charges performed, as well as its validation in a real environment and verifying the energy savings achieved.