Conceptual Implementation of LSTM-Improved LA Based Smart Electric Vehicle Battery Management System

The importance of green energy is growing in the modern world. That's why, in terms of environmental impact, electric vehicles are the best option for commuters and car owners alike. Lithium-ion batteries are commonly utilized in EVs because of their high energy and current density. Lithium-ion batteries pose a risk if used outside of their Safe Operating Area (SOA). This necessitates the incorporation of BMS technology into all lithium-ion batteries, not just those used in EVs. It delves deeply into the nature, function, and structure of BMS. A literature review also covers early battery models as well as the hardware and system architecture for BMS. The simulation results are then used to show how well the updated model of the battery performs. Preprocessing, feature selection, and model training are all included in the research article. It employs a PCC for feature selection and an LSTM- ILA for model training. The proposed method achieves better results than both the LSTM and LSTM-LA models.