State of Charge (SOC) and State of Health (SOH) estimation on lithium polymer battery via Kalman filter

Abstract

To avoid battery failure and keep the battery lifetime, a system needs control its use by considering two of several parameters of Battery Management System (BMS) such as State of Charge (SOH) and State of Health (SOH). The State of Charge in Battery Management System provides the percentage of battery capacity, while the State Of Health measures the battery health. The Thevenin battery model is used to describe polarization characteristic and dynamic behavior of the battery and estimared using KalmanFilter(KF). Parameters in the model were estimated using Recursive Least Square. As the results, KF is better then RLS to estimate SOH with a mean relative error as much as 5.26% while RLS has 7.08%.