Department of EEE, IIT GUWAHATI
Talk title: Synergy of Physics-informed machine learning and Fractional-order control for Next-Gen batteries
Abstract:Integer-order equivalent circuit physics-based models, defined by ideal capacitors and inductors may not accurately capture the battery behaviour when the relationship between voltage and current is not precisely an integral derivative. These “non-ideal” relationships, such as solid phase diffusion, charge transfer reaction and double layer effect in battery dynamics can be captured by a fractional-order capacitor. This talk discusses the potential of integrating fractional-order physics-based models with machine learning models to estimate energy storage performance. The idea is to develop a cutting-edge technology to deliver an improved predictive accuracy with decreased computational cost and enhanced physically meaningful information in battery diagnostics.