Battery state and internal variables estimation using a reduced-order physics-based model of a lithium-ion cell and a nonlinear Kalman filter - (PPT)

摘要

There are potential benefits that can be realized by battery controls that use physics-based models of cells (vs. circuit models) These controls require knowledge of the cell internal electrochemical state, which cannot be measured in an application In this paper, we have demonstrated that a nonlinear Kalman filter is able to estimate these internal states, with the aid of a physics-based reduced-order model of cell behaviors EKF produces reliable estimates and error bounds for SOC and all internal electrochemical variables (SPKF gives similar results) This is encouraging: It opens up the possibility of future improved battery management methods.