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

摘要

1. There are potential benefits that can be realized by battery controlsrnthat use physics-based models of cells (vs. circuit models)rn2. These controls require knowledge of the cell internalrnelectrochemical state, which cannot be measured in an applicationrn3. In this paper, we have demonstrated that a nonlinear Kalman filterrnis able to estimate these internal states, with the aid of a physicsbasedrnreduced-order model of cell behaviorsrn4. EKF produces reliable estimates and error bounds for SOC and allrninternal electrochemical variables (SPKF gives similar results)rn5. This is encouraging: It opens up the possibility of future improvedrnbattery management methods.