The Department of Electrical and Electronics Engineering of Paavai Engineering College organized an Online Guest Lecture on “Prediction of RUL of Battery – A Machine Learning Approach for Sustainable Transportation” on 10 April, 2024. Dr.K.Karthick, M.E., Ph.D., Associate Professor, Department of Electrical and Electronics Engineering, GMR Institute of Technology, Rajam, Andhra Pradesh was the resource person. The welcome address was given by A.Nisha, 3rd year EEE and Chief Guest introduction given by R.Janani, 3rd year EEE. The resource person explained about the systematic navigation through challenges in predicting the RUL values of Li-ion batteries, emphasizing the significance of ML approaches. Various ML algorithms were evaluated, with XGBoost demonstrating superior performance in RUL prediction. The results highlighted the efficacy of the XGBoost algorithm in minimizing errors and accurately predicting RUL. These findings are instrumental for both manufacturers and owners, fostering efficient trip planning and facilitating the development of longer-lasting batteries, he further explained. He also gave inputs about research works on the transformative intersection of technology and industry, paving the way for sustainable advancements in electric vehicle infrastructure. Considering the focus on sustainable development and the environmental impact of electric vehicles, there could be a hypothesis that could accurately predict RUL contribution to extending battery lifespan, thereby reducing the environmental concerns associated with battery disposal.
The Head of the Department, Faculty members and Students have participated the session and benefitted. The Vote of thanks was delivered by N.Pooja, 3rd year EEE in the end. Dr.G.Balaji, Prof and Head/EEE, Dr.A.Rathinam, Prof/EEE, and R.Muthukumar Assistant Professor/EEE took care of the arrangements required to organize the program. The master of ceremony was taken care by S.Nathiya and M.Kavipriya 3rd year EEE.
