AI driven real-time battery SOC estimation with intelligent power control
This paper presents an integrated hardware–software framework for real-time SOC estimation and intelligent power control using a machine learning approach and demonstrates high prediction accuracy with a mean absolute error of 0.0062% and R2 of 99.9997%, outperforming conventional and deep learning-based approaches.