Artificial Intelligence and IoT based Smart Battery Management System for Electric Vehicle
Shradha Umathe, Rutuja Hiware
Abstract
The battery of an electric vehicle is critically essential. As a result, thorough battery maintenance is essential to ensure that it continues to operate properly. The lead-acid battery is taken for this research, which is the most common type of battery used in an electric vehicle. The battery must be thoroughly inspected to ensure that they work optimally under all circumstances. Controlling the operation of battery systems is critical to ensuring their overall safety, dependability, and performance. It is necessary to implement a more organized battery management system to keep track of the battery's performance. The Internet of Things (IoT) is used to collect and track battery statistics in the cloud, which are then analyzed. The ThingSpeak makes it feasible to collect and analyze battery-related data in the cloud. When it comes to batteries, the most important thing to consider is their present State of Charging (SoC). To predict the SoC, current, voltage, and temperature must all be measured. It is possible to anticipate the SoC of the battery by utilizing a deep learning model called a Recurrent Neural Network (RNN). The difference between the anticipated SoC and the actual SoC is used to determine how well the RNN model performs.