Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm

Abstract

Purpose: The purpose of this study is to create a new fuel flow rate model adopting cuckoo search algorithm (CSA) for the climbing phase of the flight. Design/methodology/approach: Using the real flight data records (FDRs) of B737-800 passenger aircraft, a new fuel flow rate model for the climbing phase of the flight was developed by incorporating CSA. In the model, fuel flow rate is given as a function of altitude and true airspeed. The aim is to create a model that yields results that are closest to the real fuel flow rate values obtained from flight data records. Various error analysis methods were used to test the accuracy of the obtained values. Finally, the effect of change of some CSA parameters on the model was investigated. Findings: It was observed that the derived model is able to predict real fuel flow rate values with high accuracy. It has been deduced that increasing the number of nest (n) and discovery rate of alien nests (pa) values of CSA parameters to a certain value gradually decreases the model’s accuracy. Practical implications: This model is considered to be useful in air traffic management decision support systems, simulation applications, aircraft trajectory prediction models and aircraft performance modelling studies because of the high accuracy accomplished by the CSA model. Originality/value: The originality of this study is the development of a new fuel flow rate model using CSA as a first attempt in the literature. The use of real flight data is important for the originality and reliability of the model.