Fractional Differential Equation Physics-Informed Neural Network and Its Application in Battery State Estimation

This article presents a novel approach using a physics-informed neural network (PINN) incorporating fractional differential equations for battery state estimation. The use of fractional calculus suggests an attempt to model complex battery behavior more accurately than traditional methods. The application to battery state estimation is a practical and relevant area. The source, ArXiv, indicates this is a pre-print or research paper, suggesting the work is likely cutting-edge but not yet peer-reviewed.