Nonlinear State and Parameter Estimation for Li-ion Batteries with Thermal Coupling

Abstract

Advanced Lithium-ion battery management systems rely on accurate cell-level state of charge (SOC) and parameter estimation for safe and efficient real-time monitoring. However, the design of combined state and parameter estimators that are provably convergent is notoriously difficult. A robust observer framework based on a coupled equivalent circuit-thermal model for a cylindrical battery is proposed. The coupled model also takes into account SOC and temperature-dependent electrical parameters for higher accuracy. In the literature, the model parameters are often treated as constants to simplify model structure and observer analysis. The problem considered in this work is particularly challenging due to (i) nonlinear two-way coupling between electrical and thermal sub-models, and (ii) nonlinear dependence of model parameters on the system states. A single aggregated observer for both SOC and thermal estimation becomes intractable due to lack of convergence certification caused by complex model coupling. We tackle this problem by proposing a sequential estimation scheme such that every sub-estimator converges separately, which is mathematically verified by Lyapunov stability analysis. Simulation results demonstrate the performance of the proposed state and parameters estimation framework.