Modeling of fuel flow-rate of commercial aircraft for the descent flight using particle swarm optimization

Abstract

Purpose: The purpose of this paper is to create a new fuel flow rate model for the descent phase of the flight using particle swarm optimization (PSO). Design/methodology/approach: A new fuel flow rate model was developed for the descent phase of the B737-800 aircraft, which is frequently used in commercial air transport using PSO method. For the analysis, the actual flight data records (FDRs) data containing the fuel flow rate, speed, altitude, engine speed, time and many more data were used. In this regard, an empirical formula has been created that gives real fuel flow rate values as a function of altitude and true airspeed. In addition, in the fuel flow rate predictions made for the descent phase of the specified aircraft, a different model has been created that can be used without any optimization process when FDR data are not available for a specific aircraft take-off weight condition. Findings: The error analysis applied to the models showed that both models predict real fuel flow rate values with high precision. Practical implications: Because of the high accuracy of the PSO model, it is thought to be useful in air traffic management, decision support systems, models used for trajectory prediction, aircraft performance models, strategies used to reduce fuel consumption and emissions because of fuel consumption. Originality/value: This study is the first fuel flow rate model for descent flight using PSO algorithm. The use of real FDR data in the analysis shows the originality of this study.