MORE | Spring 2025

Hybrid AI-Driven SOC and SOH Estimation for Battery Management Systems

This research aims to develop a hybrid AI-driven approach for State of Charge (SOC) and State of Health (SOH) estimation in battery management systems by integrating physics-based models with machine learning algorithms. This hybrid methodology enhances estimation accuracy, improving battery lifespan, reliability, and safety. The approach optimizes energy storage performance in electric vehicles (EVs) and grid-scale Battery Energy Storage Systems (BESS). Future work will focus on refining the hybrid framework and expanding its applicability across diverse battery chemistries and operating conditions.