Prognostics for Lithium-ion batteries for electric Vertical Take-off and Landing aircraft using data-driven machine learning

The health management of batteries is a key enabler for the adoption of Electric Vertical Take-off and Landing vehicles (eVTOLs). Currently, few studies consider the health management of eVTOL batteries. One distinct characteristic of batteries for eVTOLs is that the discharge rates are significantly larger during take-off and landing, compared...

Probabilistic Flight Delay Predictions Using Machine Learning and Applications to the Flight-to-Gate Assignment Problem

The problem of flight delay prediction is approached most often by predicting a delay class or value. However, the aviation industry can benefit greatly from probabilistic delay predictions on an individual flight basis, as these give insight into the uncertainty of the delay predictions. Therefore, in this study, two probabilistic forecasting...

Assessing strategic flight schedules at an airport using machine learning-based flight delay and cancellation predictions

To mitigate air traffic demand-capacity imbalances, large European airports implement strategic flight schedules, where flights are assigned arrival/departure slots several months prior to execution. We propose a generic assessment of such strategic schedules using predictions about arrival/departure flight delays and cancellations. We...