Estimating State of Energy in Lithium-ion Batteries Using a Super-Twisting Algorithm-Based Sliding Mode Observer*

The state of energy (SoE) is a critical metric for battery management systems, complementing the state of charge (SoC) in providing comprehensive battery management insights. This paper addresses SoE estimation for lithium-ion batteries by designing a sliding mode observer that utilizes sliding mode control technology to enhance the robustness of the SoE estimation algorithm. Leveraging the correlation between SoC and SoE, this study develops a method to accurately estimate SoC and determine SoE. Additionally, we introduce a sliding mode observer based on the Super-twisting algorithm, which stabilizes the observer by carefully selecting parameters. The effectiveness of the proposed SoE estimation algorithm is validated using Dynamic Stress Test (DST) data, confirming its practical utility.