Electrode-Level State Estimation in Lithium-Ion Batteries via Kalman Decomposition

Lithium-ion battery electrode-level online state estimation using high-fidelity nonlinear electrochemical models remains a key challenge. This is particularly due to weak observability inherited from the complex model structure, even for reduced-order models. letter presents systematic and rigorous strategy analyze local of single particle (SPM) with both electrodes, which commonly known be locally unobservable current-voltage measurements. Estimating essential states, e.g., charge (SOC) solid-phase lithium surface concentration, crucial health monitoring since different degradation mechanisms affect each electrode individually. In this letter, proposed analysis approach based on Kalman decomposition enables provably convergent estimates. Ultimately, analysis, we propose estimator SPM dynamics prove error system stability. The scheme exploits conservation property. Simulations demonstrate effectiveness as opposed cell-level estimator.