Abstract
In the performance analysis of an aircraft, the takeoff weight is an important parameter since it directly influences the force equilibrium in flight conditions. Along with the takeoff weight, if flight trajectory and fuel flow characteristics are also available or accurately estimated for a flight, flight performance can be improved by analyzing the data. Due to the airline policies regarding access to flight data, gross weight, fuel consumption, and other aircraft sensory data are challenging to obtain. For that reason, estimating the aircraft weight from surveillance data such as ADS-B is crucial in analyzing aircraft performance characteristics. In this paper, a generalizable machine-learning approach to estimate aircraft takeoff weight with the extracted features from different phases of the trajectory data for three different types of wide and narrow-body aircraft is proposed. The feature extraction process and the validation of the model with ground truth data are performed using the Quick Access Recorder (QAR) data. The evaluation of the method is carried out by creating four different machine-learning models and comparing the mean absolute percentage errors (MAPE) on the test set. Two case studies are analyzed by training models with single aircraft and three different aircraft having distinct takeoff weights to demonstrate that the model is generalizable. The best result is obtained using Extra Trees Regressor for the multiple aircraft case with a mean absolute percentage error and standard deviation of 1.48% TOW and 2.12% TOW, respectively.
Original language | English |
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Title of host publication | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023 |
Publisher | American Institute of Aeronautics and Astronautics Inc, AIAA |
ISBN (Print) | 9781624107047 |
DOIs | |
Publication status | Published - 2023 |
Event | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023 - San Diego, United States Duration: 12 Jun 2023 → 16 Jun 2023 |
Publication series
Name | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023 |
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Conference
Conference | AIAA Aviation and Aeronautics Forum and Exposition, AIAA AVIATION Forum 2023 |
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Country/Territory | United States |
City | San Diego |
Period | 12/06/23 → 16/06/23 |
Bibliographical note
Publisher Copyright:© 2023, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.