StorkJet has secured EU funding to accelerate its R&D applying machine learning to a quiet but persistent source of inefficiency in flight operations: inaccurate aircraft performance models. 

Operational systems today – from flight planning to EFB and fuel management tools – can apply only a single performance correction per aircraft, because more granular data has not existed. But the gap between model and reality is not constant: it changes with weight, altitude, speed and temperature. 

That is what we are setting out to model – multidimensional corrections that reflect how each individual aircraft actually performs across its whole operating envelope. 

For airlines, this means: 

• more precise fuel planning 
• lower fuel burn and CO₂ emissions 
• higher operational efficiency and improved safety 

The models will be verified in operational conditions, as well as prepared for integration with the flight planning and other systems airlines already use, with globally operating carriers as the target.

Yet another step toward safer, greener and more efficient flight operations! 

Total project value: 2.5 million EUR

EU funding: 1.6 million EUR

StorkJet’s contribution: 910 thousand EUR