Li-ion battery modeling and SOC estimation using extended Kalman filter

Lithium ion batteries are preferred especially in electric car applications over other types of batteries thanks to their intrinsic safety, capacity for fast charging and long cycle life. In order to get an accurate battery model, it is important to be able to determine a couple of state parameters such as state of charge and state of health. In this work, battery management system algorithms were improved for generic Lithium ion battery state of charge estimation using Matlab Simulink. First, an equivalent circuit battery mathematical model was developed with the aim of simulating the behaviour of a lithium-ion battery as accurately as possible. The Thevenin model is achieved by adding an extra RC branch and the model parameters are identified employing the Extended Kalman Filter (EKF). In this work, it is aimed to catch the battery characterization and provide the correct parameters to the Kalman Filter code in order to accurately estimate the SOC.