Hybrid Machine Learning Model for EV Battery SoC and SoH Prediction

As electrification advances in the automotive industry, attention towards the safety and reliability of the battery becomes important. The Battery Management System (BMS) which is the heart of the whole Battery system needs to be periodically inspected to ensure the safety, reliability, and longevity of EVs Li-ion batteries. Therefore, the study covers different hybrid machine learning (ML) approaches for monitoring remaining charge and EV battery health through hybrid machine learning (ML) such as LSTM-SVR, LSTM-ARIMA and LSTM-ATTENTION in two different platforms PYTHON IDLE and RASPBERRYPI 4B and ultimately suggest the best ML Hybrid Model to determine the state of charge and health of the battery.