The shared goal was to strengthen knowledge exchange on the development of battery digital twins and to identify common technical challenges, opportunities for collaboration and future standardisation needs.
The workshop featured short technical presentations from both projects, followed by an interactive roundtable.
Marion Chandesris from CEA presented THOR’s methodology for reducing the experimental effort required to parameterise physics-based electro-thermal battery models while maintaining high prediction accuracy.
From the BATMAX consortium, Jacob Hadler-Jacobsen and Håkon Pedersen from SINTEF presented BATMAX work on Li-ion battery degradation prediction using physics-informed neural networks, showing how hybrid modelling approaches can exploit both physical knowledge and machine learning techniques to improve degradation prediction with limited experimental datasets. Then Prashant Singh from VTT presented the implementation of a real-time Hardware-in-the-Loop platform capable of emulating battery behaviour, validating Battery Management System functions and transmitting operational data to cloud-based digital infrastructures.
The industrial perspective was brought by Antonio Gabriele from Flash Battery, who illustrated how industrial battery manufacturers can contribute real-world operational data to improve digital twins. Battery Management Systems data play an important role in supporting both predictive digital twins and the emerging Digital Battery Passport. However, several open challenges remain, particularly regarding State-of-Health reporting, data ownership and update frequency.
Miguel Aranda from UNE presented the opportunities for translating project outcomes into European standardisation activities. Potential topics identified included intelligent ageing methodologies, interoperability of battery data, ontologies, common information models and harmonised approaches to State-of-Health assessment, which is currently emerging as a priority topic within IEC standardisation activities.
The roundtable highlighted a strong convergence between THOR and BATMAX, with both projects agreeing that that reliable digital twins require a combination of robust physics-based models, high-quality data, rigorous experimental validation and harmonised data management throughout the battery lifecycle.
Among the key topics discussed, battery parametrisation emerged as one of the main technical challenges. Reducing the experimental effort required while preserving model accuracy remains a common objective, with hybrid approaches combining experimental measurements, physics-based models and data-driven techniques identified as the most promising path forward.
Another recurring theme was the importance of operational Battery Management System data. While laboratory testing provides the foundation for model development, participants agreed that real-world operational data is essential to validate digital twins, accurately capture battery ageing and enable continuous model refinement. The discussion also highlighted that the quality and reliability of data are ultimately more important than the sheer volume collected.
The workshop further explored the close relationship between digital twins and the emerging Digital Battery Passport. Both rely on many of the same datasets—particularly BMS data—but their successful implementation will require addressing key challenges related to data governance, ownership, confidentiality and the harmonisation of State-of-Health indicators.
Standardisation was identified as another critical enabler. Participants agreed that common ontologies, harmonised data models and interoperable information structures will be essential for creating a connected European battery ecosystem.
Overall, the workshop successfully strengthened collaboration between THOR and BATMAX, highlighting significant synergies in battery modelling, digital twins, artificial intelligence and data interoperability. Beyond the exchange of technical expertise, it provided a valuable opportunity to compare methodologies, share lessons learned and explore how data-driven approaches can accelerate battery innovation while supporting emerging European initiatives such as the Digital Battery Passport.