Data-Driven Approaches to Minimize Battery Testing & Improve Degradation Modeling
“oorja’s platform transformed our cycler data post-processing workflow by integrating data-driven and physics-based hybrid modeling. We were able to calibrate Beginning-of-Life and degradation models in under a month, and—critically—track the evolution of key model parameters that were previously almost impossible to monitor. This has significantly deepened our understanding of battery behavior and accelerated R&D.”
~ Dr. Shruti Srivastava,
Senior Engineer, Scania
Can You Predict Battery Degradation Reliably Without Extensive Testing? oorja Says Yes!
As battery systems become more intricate, a deep understanding of their performance is crucial. Yet, the high cost of comprehensive experimental testing presents a significant challenge. What if there’s a better way?
Join our webinar to see how Scania is achieving efficiency by utilizing oorja’s hybrid (physics + ML) predictive analysis to optimize their battery testing and modeling strategy. We’ll demonstrate how oorja’s hybrid modeling approach—combining the strengths of physics-based modeling and machine learning—streamlines cycle life testing optimization, saving time and resources.
Key Takeaways:
- Training Efficacy: Understanding the impact of training data volume and quality on prediction accuracy.
- Optimizing Testing: Improving test protocols- better efficiency and improved data handling.
- BoL Optimization: Optimizing BoL parameters, ensuring more reliable degradation predictions by accounting for parameter interplay.
- Insights from Data Analysis
Meet The Speakers
Prashant has fifteen years of experience in the Computer-Aided Engineering (CAE) field and holds a PhD in Aerospace and Astronautical Engineering from the Indian Institute of Science (IISc).
Dr. Shruti Srivastav is a senior engineer at Scania CV AB, where she leads simulation-driven research and development in battery systems, focusing on parameter optimization, degradation prediction, and system integration. With over a decade of experience spanning battery science, electrochemical modeling, and AI-enabled simulation, she has held key roles at COMSOL and Uppsala University and actively contributes to Nordic battery innovation initiatives. Shruti is passionate about sustainable transport and the use of digital tools to accelerate the next generation of energy storage technologies.