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Physico-chemical models are key for a successful use of lithium-ion batteries, especially under extreme conditions. For correctly simulating of the internal battery states and battery aging a suitable set of material properties is needed. This work presents methods to extract these parameters from commercial cells and demonstrates them analyzing a high-power prismatic cell. In a first step, the electrolyte analysis is described, followed by an examination of the active material. The composition as well as the porous structure are measured using optical emission spectroscopy and Hg-porosimetry. To determine the electrochemical properties of the electrode materials, coin cells with lithium as counter electrode are build. With these test cells, open circuit voltage curves and galvanostatic intermittent titration technique measurements are performed to determine the electrode balancing as well as the diffusion constants of the active material. Electrochemical impedance spectroscopy experiments on the full cell are used to determine the charge transfer. In the second part of this paper, a determination of the thermal parameters as well as a validation for the complete parameterization are described.

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As lithium-ion batteries play an important role for the electrification of mobility due to their high power and energy density, battery lifetime prediction is a fundamental aspect for successful market introduction.This work shows the development of a lifetime prediction model based on accelerated aging tests. To investigate the impact of different voltages and temperatures on capacity loss and resistance increase, calendar life tests were performed. Additionally, several cycle aging tests were performed using different cycle depths and mean SOC. Both the calendar and the cycle test data were analyzed to find mathematical equations that describe the aging dependence on the varied parameters. Using these functions an aging model coupled to an impedance-based electrical-thermal model was built. The lifetime prognosis model allows analyzing and optimizing different drive cycles and battery management strategies. The cells modeled in this work were thoroughly tested taking into account a wide range of influence factors. As validation tests on realistic driving profiles show, a robust foundation for simulation results is granted.Together with the option of using temperature profiles changing over the seasons, this tool is able to simulate battery aging in various applications.

Physico-chemical models allow a deep view into the internal processes and states of lithium-ion batteries. A crucial part of such models is the correct parameterization of the cell under consideration. In the first part of this publication methods to determine physical and electrochemical parameters are described and the experimental results from a PHEV cell are given. As the cell shows significant self-heating, a simple thermal model is introduced and the thermal parameters of the cell are determined. After a summary of all identified parameters a validation of these input data and the model is given. A wide range of measurements is compared to simulation results. This includes discharges at different temperatures and current rates as well as pulse tests and a realistic driving profile.

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