Loading...
Dr. N. Muguntha Manikandan is a Professor in the Department of Physics at VSB Engineering College, Karur, Tamil Nadu, India. His research interests include Energy Materials, Electric Vehicle Technologies, Applied Physics, and Sustainable Energy Systems.
Electric Vehicles (EVs) are fundamental to sustainable transportation, with battery performance significantly influencing vehicle efficiency, safety, reliability, and driving range. Battery Management Systems (BMS) are crucial for overseeing, regulating, and enhancing battery functionality throughout their lifespan. Conventional Battery Management System methodologies frequently encounter difficulties in precisely assessing battery states, forecasting degradation, and regulating intricate charging and discharging scenarios. Artificial Intelligence (AI) has arisen as a potent option for optimising battery management via sophisticated data analysis, predictive modelling, issue detection, and real-time decision-making. Through the integration of machine learning, deep learning, Internet of Things (IoT), cloud computing, and digital twin technologies, AI-driven Battery Management Systems (BMS) can optimise battery health, prolong lifespan, augment energy efficiency, and guarantee operational safety. This chapter examines the designs, methodology, applications, problems, and future trajectories of AI-enhanced Battery Management Systems for electric vehicles.