Imagine your car battery had a digital twin in the cloud that knew exactly how it was aging and why. Instead of guessing when a battery is worn out, this system uses smart sensors and AI to predict its health. This allows batteries to be safely reused for home energy storage after they are too old for cars.
Current battery management systems rely on simple models and limited data, leading to inefficient use of batteries and uncertainty regarding their safety and remaining life, especially when transitioning to second-life stationary storage.
A Hardware Abstraction framework for embedded devices to process sensor signals and a cloud-connected digital twin using AI for battery diagnosis and prognosis.
If you are an EV manufacturer dealing with unpredictable battery degradation and safety risks—this project developed a next-generation BMS that uses AI and multiphysics models to ensure safer operations and more accurate state estimation.
If you are a stationary storage provider dealing with the uncertainty of using old EV batteries—this project developed a digital twin that monitors the remaining useful life of second-life batteries to optimize their use in the grid.
If you are a hardware developer dealing with limited on-board processing power for complex battery data—this project developed a Hardware Abstraction framework for embedded devices to deliver sensor signals to the cloud.
Based on available project data, specific pricing or implementation costs are not provided.
The project involves 8 industrial partners and focuses on cloud and edge computing, suggesting a design intended for industrial scalability.
Based on available project data, there is no specific information regarding the licensing model or patent strategy.
It uses a Hardware Abstraction framework on embedded devices to bridge battery sensor signals with upper network layers.
The project runs from 2023-06-01 to 2026-08-31, indicating that final results will be available by late 2026.
The project is balanced with a 50% industry ratio, consisting of 8 industrial partners (including 4 SMEs) and 8 universities across 8 countries. This structure ensures that the academic research into AI and multiphysics models is directly aligned with commercial needs in the battery and transport sectors.
Contact the Institut National des Sciences Appliquées, Strasbourg
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