Set-Valued Approach for the Online Identification of the Open-Circuit Voltage of Lithium-Ion Batteries

To describe the dynamic behavior of lithium-ion batteries using the terminal current and the terminal voltage as input and output of the battery, equivalent circuit models are used, which comprise series resistances, RC sub-networks and a state of charge dependent voltage source. The parameters of the battery model are influenced by aging effects as well as other factors such as the state of charge and the cell temperature. Although those variations can be estimated with the help of an augmented state vector, the typically applied approaches do not allow for a direct identification of nonlinear dependencies of circuit elements on the state of charge or other influence factors. Therefore, a two-stage identification routine for identifying those nonlinear dependencies using an interval observer and an interval contraction scheme is proposed in this paper. The identification routine was successfully applied to identify the open-circuit voltage characteristic of a lithium-ion battery. Numerical simulations are used to evaluate the identification quality of the identification routine.