Electric Vehicle's Range and State of Charge Estimations using AutoML

This paper examines the potential of AutoML for predicting the range and State of Charge (SOC) of Electric Vehicles (EVs). Unlike traditional SOC estimation methods, such as Coulomb counting, Equivalent Circuit Models (ECM), or Machine Learning (ML)-based approaches, Range Estimation Algorithms (REA) consider route-specific factors to offer more precise battery depletion predictions. However, ML-based REAs can be complex and time-consuming to …