Stephan Bihn

Vertical temperature gradients can occur in prismatic high-power lithium-ion cells under high-current operation and asymmetric thermal boundary conditions. This work has investigated their effect on the terminal electrical response of an automotive-grade prismatic high-power nickel-manganese-cobalt lithium-ion cell. Electrochemical impedance spectroscopy (EIS) and 10 s pulse measurements have been performed under homogeneous and vertical-gradient conditions, with pulse currents reaching up to 15C. Homogeneous measurements have covered temperatures from -20 to 40 °C and State-of-Charge (SoC) levels from 10 to 90 %. Vertical gradients of 10, 20, and 30 K have been applied around mean boundary temperatures of 5 °C and 25 °C. Under homogeneous conditions, impedance magnitude has shown the highest temperature sensitivity below approximately 1 Hz, while phase has shown the highest temperature sensitivity between 10 and 100 Hz. Temperature effects have exceeded SoC effects across most of the spectrum. Under vertical gradients, EIS spectra and pulse responses have closely matched homogeneous references at an effective mean cell temperature, without distinct gradient-specific signatures. A complete repeat of the experimental campaign on a second cell using an independently assembled, equivalent setup has shown comparable results. Terminal measurements alone therefore cannot reliably identify vertical temperature gradients, motivating additional thermal sensing or thermo-electric modeling for gradient-aware power prediction.

This work introduces a sophisticated impedance-based equivalent circuit model of the electrochemical processes inside a lithium-ion battery cell. The influence on the electrical voltage response is derived and merged into a mathematical calculation framework describing all fundamental phenomena inside a battery. The parameters, whose sole influences on the electric behaviour cannot be separated at the cell level, are summarised to derive a model with purely electrical quantities. We significantly reduce the model order compared to a physicochemical model while ensuring a minimal approximation error. Utilising the findings from the model derivation, we develop a parameterisation procedure to separate the individual processes occurring in the battery and to support a hypothesis of the assignment to positive and negative electrodes based on several indicia. For this purpose, electrochemical impedance spectroscopy and correlation analysis are used to calculate the distribution of the time constants. The final parameterised model has physics-based parameter variations, which ensures that the simulation over broad ranges of temperatures and states of charge results in a reasonable voltage response. The model’s physical basis enables extrapolation beyond the measured operation area, and the model verification shows less than a 10 mV root mean square error over a wide range of operations.