Experiment-driven electrochemical modeling and systematic parameterization for a lithium-ion battery cell

This paper presents a novel electrochemical lithium-ion cell model which can be used in battery control units. Based on classical single-particle approaches, a lumped-parameter nonlinear model is developed that is able to predict accurately the terminal voltages for arbitrary loads, and even for potentiostatic operation. The key points are: (1) an incorporation of the electrolyte potential, (2) a modal decomposition of the partial differential equation of the liquid phase lithium-ion concentration, (3) a correct handling of the SOC-dependent diffusivity in the insertion materials of both electrodes, and (4) a consideration of temperature-dependent kinetic processes. A combined parameter analysis and identification is successfully applied for the parameterization of the model. Using a Fisher-information matrix approach in combination with a sensitivity analysis, the identifiability of each parameter is estimated in dependence on the measurement information. Using this information, it is possible to choose a small number of relevant experiments which are sufficient to fully parameterize the model.