Estimating the State of Health of Lithium Ion Batteries using Neural Networks

With the world steadily transitioning to use electric vehicles, a new problem arises as for how batteries can be better maintained. Their maintenance requires a fully featured battery management system that can optimize the usage of these batteries for longer lifespans. One of the functionalities that could be useful is predicting the state of health of a lithium-ion battery. This paper explains how a model can be built to predict the Remaining Useful Life (RUL) of a battery by estimating the State of Health (SoH) of the battery using a neural network with given resistance measurements of a lithium-ion battery.