Research Areas
Our research is structured into three complementary areas that together create the scientific foundation for next-generation battery safety and lifecycle optimization. From predictive modeling and degradation analysis to intelligent monitoring and failure prognosis, we combine physics-based understanding, advanced characterization, and data-driven methods to enable safe, efficient, and sustainable energy storage systems.
Area 1
Prediction and Optimization
Area 1 focuses on developing advanced models and simulation methods to predict, optimize, and improve the safety and performance of battery cells and systems. By combining multi-physics modeling, virtual development, and research on next-generation battery technologies, it reduces testing effort and accelerates reliable battery design across the entire lifecycle.
Area 2
Degradation Mechanisms
Area 2 investigates the aging and degradation mechanisms of battery systems and safety-relevant components, developing predictive models and accelerated aging methods that link degradation to safety-critical thresholds in order to reliably assess and forecast changes in safety margins over the entire battery lifetime.
Area 3
Monitoring and Failure Prognosis
Area 3 develops diagnostic strategies and physics-based as well as data-driven models to monitor battery state and define a State of Safety (SOS), enabling the prediction of safety evolution and Remaining Safe Useful Life (RSUL) in order to support early risk detection, predictive maintenance, adaptive operation, and optimized second-life deployment.
