Systems and methods for machine learning enabled fault detection in rechargeable batteries

Abstract

In one aspect, computer-implemented method may include receiving, at a cloud-based computing system, a set of measurements over a certain period of time. The set of measurements are received from a set of vehicles and pertain to voltages and temperatures of a set of battery packs associated with the set of vehicles. The method may include training, using the set of measurements, one or more machine learning models to predict a battery pack fault condition. The one or more machine learning models include a set of parameters that are modified during the training. The method may include transmitting the set of parameters to the set of vehicles to enable the set of vehicles to update, based on the set of parameters, one or more respective in-vehicle machine learning models configured to predict the battery pack fault condition.