Evaluation and observability analysis of an improved reduced-order electrochemical model for lithium-ion battery

Abstract

Abstract The accurate modeling of lithium-ion battery is helpful for developing advanced battery management system (BMS) and monitoring battery states. Despite the electrochemical model (EM) of a battery cell has gradually become a main candidate for advanced BMS, the EM-based estimators still face a big problem regarding to the weak observability. To address this issue, this paper proposes an improved reduced-order electrochemical model (iROEM) with guaranteed observability. First, the solid phase equations are reconstructed by combing Pade approximation and polynomial fitting method, and the electrolyte concentration equations are reduced by using volume averaging technique, which ultimately contributes the development of the iROEM. Second, the observability analysis of the proposed iROEM is conducted to facilitate the control applications in BMS. Finally, the designed iROEM is evaluated by performing a comparative study of the electrolyte concentration distributions and battery terminal voltages with respect to the pseudo two-dimensional model under the constant current and dynamic working conditions. The results demonstrate that the iROEM with guaranteed observability has high model fidelity and less computational complexity, which contributes to the resultant estimators for the lithium-ion battery electrochemical model.