A novel process to determine an aircraft performance model from operational flight data with limited a priori knowledge is developed. The given big data problem is solved by application of fundamental engineering knowledge and a specific data evaluation strategy. The resulting smart data approach is fundamentally different from existing deep learning methods to solve such big data problems. A given aerodynamic model is updated to represent the characteristics of an Airbus A320neo aircraft based on a given large database of operational flights. The updated aerodynamic model implementation for one specific flap/slat configuration is exemplarily compared to the information available from flight data and the results are discussed in terms of model quality.
Aerodynamic model adjustment for an accurate flight performance representation using a large operational flight data base
CEAS Aeronaut J
CEAS Aeronautical Journal ; 14 , 2 ; 527-538
2023-03-01
12 pages
Article (Journal)
Electronic Resource
English