Drag polar modelling for jet aircraft using 6-DOF model data via cuckoo search algorithm

Abstract This paper describes a reverse engineering methodology so as to accomplish an aero-propulsive modelling (APM) through implementing a drag polar estimation for a case study jet aircraft in case of the absence of the thrust data of the aircraft’s engine. Since the available thrust force can be replaced by the required thrust force for the sustained turn, this approach allows the elimination for the need of the thrust parameter in deriving an aero-propulsive model utilising equations of motion. Two different modelling approaches have been adopted: (i) implementing the 6-DOF model data for sustained turn and climb flight to achieve induced drag model; and then incorporating the glide data to obtain the total drag polar model; (ii) using the 6-DOF model data together with introducing the effect of C L - α dependency. The error assessments showed that the derived CSA models were able to predict the drag polar values accurately, providing linear correlation coefficient ( R ) values equal to 0.9982 and 0.9998 for the small α assumption and C L - α dependency, respectively. A direct comparison between the trimmed C D values of 6-DOF model and the values predicted by the CSA model was accomplished, which yielded highly satisfactory results within high subsonic and transonic C L values.