Testing a new battery usually takes forever because you have to wait months or years to see if it fails. Imagine if you had a high-tech digital mirror of the battery that could predict the future and tell you the result in days instead of years. This project builds those digital mirrors and a common language so different labs can share data instantly.
Battery testing is currently too slow, expensive, and fragmented, often requiring tests that last for years to fully characterize a cell.
An open standard for battery test data, BattINFO-based metadata schemas, and a digital twin system using Functional Mock-up Units (FMUs) for real-time simulation.
If you are an EV manufacturer dealing with slow battery validation cycles — this project developed digital twin workflows that reduce the experimental burden. This allows for faster data-driven decision-making during vehicle powertrain simulation.
If you are a ship builder dealing with expensive long-term battery safety tests — this project developed Functional Mock-up Units (FMUs) for marine powertrain simulations. This enables plug-and-play digital twin deployment to predict lifetime and safety.
If you are a Gigafactory dealing with fragmented and expensive testing data — this project developed an open community-driven standard for battery test data. This ensures your data is FAIR compliant and easily exchangeable across the value chain.
Based on available project data, it extracts more value from fewer tests, reducing the time and resources spent on destructive and non-destructive tests that can otherwise last for years.
The project aims to move the technology from TRL 4 to TRL 6, with current progress including the deployment of metadata schemas and FMUs for vehicle and marine simulations.
Based on available project data, the project has released an open, community-driven standard for battery test data to ensure interoperability.
Yes, the project's achievements in data semantics and FAIR compliance are designed to support alignment with EU battery passport requirements.
Integration is achieved via Functional Mock-up Units (FMUs), allowing the digital twins to be plugged into system-level simulations.
The consortium is well-balanced for commercialization, consisting of 9 partners across 5 countries. With a 33% industry ratio (3 industrial partners, including 2 SMEs), the project bridges the gap between 6 research/university entities and actual Gigafactories and integrators, ensuring the digital tools are grounded in industrial reality.
Contact SINTEF AS in Norway for technical specifications on the digital twin workflows.
Contact us to find the specific FMU integration guides for your powertrain simulation.
