ARCHIMEDES

The transformation of the automotive, aerospace and infrastructure landscapes and associated ecosystems towards a resilient, decarbonized, digitized and green EU requires building confidence in the extended lifetime and system durability of new and high efficiency technologies. Currently, it is unclear if high efficiency wide bandgap technologies can achieve the required lifetime. The situation is further complicated by today's qualification procedures, which take a very long time relative to the expected lifetime and are not covered by in-service lifetime verification. Here, ARCHIMEDES will advance the state-of-the-art.

Within the project SAL contributes research in the following areas:

Research on data-driven health prediction

SAL will use early engineering examples of electrochemical impedance spectroscopy (EIS) chips to conduct research on AI approaches for improved estimation of the health of the aircraft propulsion battery during operation and charging. 

Research on verification methods for extended life

Current verification standards are mostly designed for a component lifetime of 8000 hours. In this project, we want to extend this limit significantly to about 120,000 hours. To achieve this goal, we are researching new validation approaches that save time compared to the current state-of-art and rely on our SAL’s Smart Validation Lab for the necessary experiments and data generation.

Research on a dependable, airworthy Battery Management System (hardware/software), including module-based charging

At the time of writing, there is no standard in aviation - especially considering the classes CS22 and CS23 - for the handling of propulsion batteries. Instead, so-called "special conditions" are used. One outcome of ARCHIMEDES will therefore be contributions to the EASA standardization process for battery management systems (BMS) for these classes. SAL wird einen Beitrag zu den Bemühungen leisten und die Forschung und Entwicklung eines neuen Batteriemanagementsystems für diese Flugzeugtypen leiten. Das BMS wird Quantensensoren mit den neuesten KI-Algorithmen kombinieren, um die Leistung des Systems zu verbessern.