In this paper, we propose a novel parameter initial value estimation method of Lithium-ion battery for state of charge (SOC) estimation by using Local Regression Modeling (LRM) and Vector Fitting (VF). To estimate SOC accurately using nonlinear Extended Kalman Filter(EKF), an adequate set of initial parameters of the battery model are required. Therefore, we apply LRM and VF method to derive the initial parameters and the battery model from a constructed database of frequency response data. In addition, we demonstrate the SOC estimation method using EKF by the determined initial value and model. Finally, the effectiveness of the proposed method is shown via several experimental results.
- Extended kalman filter
- Local regression modeling
- Vector fitting
ASJC Scopus subject areas
- Control and Systems Engineering