Interactive learning on predicting battery degradation through Python software

Abstract

The premise of interactive learning is to create engaging and effective learning experiences for participants through active participation. This report documents the approach of creating an interactive platform for students to study about battery degradation using both hardware & software. The intended learning outcomes of the designed learning platform aims to teach users about lithium-ion batteries, circuit theory and digital circuits and machine learning techniques to develop a suitable model which can predict the battery’s state of health.