Monitoring and Prediction of Battery Life in Electric Vehicle: A Comparative Study

In electric vehicles, battery management systems (BMS) are used to monitor and control the charging and discharging of rechargeable batteries, making the operation more efficient. The battery management system keeps the battery safe and reliable while increasing senility without causing damage. Lithium-ion batteries are frequently employed in electric vehicles due to their high energy and current density. Unfortunately, if lithium-ion batteries are not used within their Safety Operation Area, they can be harmful (SOA). As a result, every lithium-ion battery, especially those used in electric vehicles, must have a battery management system (BMS). The focus of this research is to monitor and predict the battery health condition using a machine learning algorithm and hence to improve the performance of the battery management system and hence extend the battery life. To improve the performance of the battery life three models are used to find out the battery’s health condition. Models used are Random Forest classifier, logistic regression, and KNN is used to find out the accurate model in which KNN with machine learning algorithm is used to predict battery heath condition.