Kalman Filter SoC estimation for Li-Ion batteries

State-of-Charge (SoC) estimation is a key factor for correct and safe battery management, particularly for the development of the Battery Management System (BMS). The paper deals with this problem for the currently most promising technology in the battery filed: Lithium-Ion batteries. An electric model of the cell is identified and verified, in order to apply Kalman Filter Theory and design an algorithm for estimating SoC. Particularly the aim of the algorithm is to reject measurement noise and parametric uncertainties and be applicable to different cells of the same manufacturer and technology. In this purpose, design criterions that speed up the convergence time or make the estimation robust to noise measurements are presented. Results on two different cells of the same manufacturer and typology are shown, focusing on the different behaviors of the estimation due to different design choices.