Abstract
Keywords: lead-acid battery, state of charge (SOC), estimation, Extended Kalman filter (EKF)
Lead-acid batteries are widely used in conventional internal combustion engine vehicles, and some electric vehicles. In order to improve the longevity, performance, reliability, density, and economics of batteries, a precise state of charge (SOC) estimation is required. Kalman filtering is one of the techniques used to determine the SOC. For a nonlinear battery model, nonlinear Kaman filters such as an extended Kalman filter and a sigma point Kalman filter are used. However, these nonlinear Kalman filters that are used in other studies are very complicated to apply to lead-acid batteries due to the complex nonlinear model of the battery. In this study, we represent a battery model with simple nonlinear equations, which can represent the battery dynamics for a non-zero battery current. Then, we applied an extended Kalman filter (EKF) method to estimate the SOC of the battery. As a result of that, we proved that the EKF can effectively estimate the SOC using the simple nonlinear battery model.