SOC and SOH estimation for Li-ion batteries based on an equivalent hydraulic model. Part I: SOC and surface concentration estimation

Accurate state-of-charge (SOC) and state-of-health (SOH) estimation is critical to ensure a reliable battery-management system (BMS). This problem is addressed here by resorting to a grey box battery model based on the so-called equivalent hydraulic model (EHM). It allows taking into account in a simple way the difference between bulk concentration and critical surface concentration (CSC) at the anode, which turns out to be significant. The dynamic model is coupled with an output equation based on the Butler-Volmer equation, and the state and parameter of the resulting nonlinear dynamic system are estimated through an extended Kalman filter (EKF). Sufficient conditions for the stability of the EKF are analysed. Finally, the results show that the method provides accurate SOC and CSC. It is shown to outperform two recently proposed approaches for CSC estimation in the considered simulation study. The CSC estimate is used in the companion paper in order to estimate the diffusion coefficient of lithium through the electrode and hence deduce a SOH indicator.