Area 2: Degradation Mechanisms

This area investigates how battery systems and key components degrade over lifetime, transforming this understanding into safer and more reliable battery technologies. Looking beyond battery lifetime and operational strategies, the research focus includes the aging behavior of critical system components such as interface materials (e.g. compression pads, thermal interface materials) and safety-relevant components (e.g. pyro fuses, sensors). 
By translating degradation understanding into advanced models and testing strategies, Area 2 supports the integration of battery lifetime considerations into system design, safety assessment, functional safety concepts, and optimized operation strategies. 

Novel degradation models will link battery aging with changes in safety-critical properties such as mechanical stiffness, thermal runaway onset temperature, and maximum intrusion depth. By identifying relevant aging mechanisms and applying physics-based modeling approaches, these models aim to enable reliable predictions and allow for a transferability between different battery systems.

Representative and accelerated aging strategies will be developed using advanced degradation models to reduce costly and time-intensive testing. These strategies systematically replicate real operating conditions while accounting for crucial factors such as battery cell inhomogeneity and relaxation effects that will be investigated in detail to guarantee representativeness. Similar approaches will be used to design procedures for other components like interface materials.

Aging modes and degradation mechanisms that evolve on different time scales will be linked with failure severity and safety thresholds (e.g., maximum intrusion depth, onset temperature for thermal runaway). Advanced post-mortem analyses and non-destructive techniques such as electrochemical impedance spectroscopy, CT scanning, or electrical characterization are used to track changes over time. These insights are integrated into degradation models to predict how safety margins change throughout a battery’s lifetime.