The Application of Kalman Filter for Lead-Acid Battery State of Charge Estimation

Abstract

Battery systems are crucial part of the most applications which are mobile and have electronic components from autonomous mobile robots to mobile phones. Hence, it is important to keep track of the state of the battery and its health in order to make these devices reliable and also protect the battery from over discharges and overcharges. There are different methods to estimate it but not all of them applicable for mobile systems. Thus, this study discusses and compares three methods that can be used for mobile applications and batteries that are under continuous use. The coulomb counting method, the linear counting model and the extended Kalman filter with nonlinear battery model are tested with both simulated and real data with a lead acid battery.