Impedance-Based Battery Health Diagnostics for Autonomous Systems Using Machine Learning
An integrated framework combining alternating current impedance spectroscopy with machine learning techniques for enhanced battery state estimation and a human–machine interface is developed to translate diagnostic results into intuitive visual outputs for decision support in autonomous cockpits.