Paper Title
A Study on Performance and Soc Estimation of Li‐Ion Batteries by using Adaptive Extended Kalman Filter
Abstract
There are various type of SOC estimation methods. Among them The Extended Kalman filter (EKF) is widely
used method to find the SOC as well as other parameters related to SOC of the Li-ion batteries system. But EKF model is
highly sensitive to disturbance and parameters error. Also this model takes long time to estimate the actual value of SOC. So,
to overcome the sensitivity error and to find the accurate SOC value, we proposed Adaptive Extended Kalman filters
(AEKF). The performance of Li-ion battery with AEKF algorithms are demonstrate by using MATLAB/Simulink as well as
some experimental results. The simulation result shows that, by using this method, the sensitivity problem due to noise is
decreased by data rejections. The results also shows that, AEKF methods can measure the exact state of charge of batteries at
different conditions and also increased the performance of the Li-ion batteries system.
Index Terms- Kalman Filter, Li-ion Battery, Equivalent Circuit Model, Open Circuit Voltage, State of Charge (SOC),