Abstract Aircraft Fuel Flow Rate Modeling for the Climb Flight Using ...

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23 Οκτ 2013 (πριν από 4 χρόνια και 8 μήνες)

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Aircraft Fuel Flow Rate Modeling for the Climb Flight Using Genetic Algorithms



Anadolu University, 26470 Eskisehir, Turkey

Fuel flow rate modeling of transport aircraft has a major importance today in terms of
reducing the envir
onmental effects of fuel emissions, saving the energy sources, flight
economy, and effective air traffic management. In this study, development of a new fuel flow
rate model for the climbing flight was achieved using genetic algorithms (GAs) method. Two
deling approaches were performed using real flight data records (FDRs) of a medium
weight transport category aircraft. First model considered the dependency of fuel
consumption with respect to only altitude, whereas the effect of both altitude and true air
(TAS) was included in the second model. The proposed modeling provides an improvement
to the existing models, since the relationship between fuel flow rate, flight altitude, and TAS
can be deduced utilizing the derived formulations. The accuracies of

both models were
evaluated by comparing the real and model derived fuel flow rate values and both modeling
approaches were concluded to provide accurate results performing an error analysis.
Regarding the first model, mean absolute percentage error (MAPE)

of 0.382, 0.337, 0.278,
0.173% were found for randomly chosen four different climb flights, respectively. The second
model provided MAPE values corresponding to the same flights as 0.261, 0.273, 0.234,
0.169%, respectively. It was seen clearly that incorp
orating the TAS effect into the second
model enhanced the accuracy of the model, but the first model was seen to be also good for
practical usage. These new non
conventional methods will be beneficial for transport
management, energy saving and environment
al studies in aviation industry; as well as for fuel
economy strategies of airline companies, and economical climb procedures development in
air traffic management.


Transport management, aircraft, fuel flow rate, climb, genetic algorithms,
ing, flight data records