Imagine trying to bake the perfect cake by baking a thousand different versions; it takes forever and wastes a lot of ingredients. This project creates a smart computer simulation that predicts how a battery will behave, so you only have to do a few real-world tests to prove it works. It's like having a digital crystal ball for battery life and safety.
Battery R&D is currently too slow and expensive due to a reliance on trial-and-error physical testing and a lack of integrated data management across test facilities.
A hybrid testing platform combining physical tests with virtual models, including a Digital Twin architecture and physics-based models for NMC/Si-C and solid-state batteries.
If you are an EV manufacturer dealing with slow prototype cycles for new battery packs — this project developed a TRL 6 hybrid testing platform that replaces time-consuming physical experiments with physics-based models to speed up time-to-market.
If you are a stationary storage provider dealing with high costs of reliability testing — this project developed optimized Design of Experiments (DoE) strategies that maximize information yield while reducing the number of physical tests needed.
If you are an off-road vehicle producer dealing with harsh environment battery failures — this project developed a Digital Twin architecture that manages data flows to create safer and longer-lasting battery designs.
It replaces expensive and time-consuming physical characterization experiments with a combination of physics-based and data-driven models. This reduces the number of tests and the need for expensive equipment.
The project aims to reach TRL 6, meaning the prototype is validated in industrial environments across automotive, stationary, and off-road use cases.
Based on available project data, specific licensing terms are not provided, but the project involves 10 industrial partners who are co-developing the platform.
It transforms local, manual operations into an interconnected system using virtualized benches and a Digital Twin architecture to manage information flows.
The project period runs from 2023-06-01 to 2026-05-31, with the final TRL 6 prototype expected by the end of this window.
The consortium is heavily industry-driven with a 56% industry ratio, comprising 10 companies (including 4 SMEs) and 8 research/academic partners across 10 countries. This strong industrial presence, led by Avesta Holding, suggests the project is focused on commercial viability and practical application rather than purely theoretical research.
Contact AVESTA HOLDING in Belgium for licensing or partnership inquiries.
Contact us to connect with the FASTEST consortium for early adoption of the hybrid testing platform.
