AIRCRAFT DRAG POLAR ESTIMATION USING CUCKOO SEARCH ALGORITHM

Effective management of air traffic will result in aircraft spending less time in the air and on the ground, thus reducing fuel consumption, fuel-related emissions, and noise levels, and increasing customer satisfaction. Aircraft performance models form the basis of an efficient air traffic management (ATM) system. In addition, drag polars are one of the most important inputs of aircraft performance models, which are important for aircraft trajectory prediction, optimization, and air traffic modeling. In this study, a simple drag polar and a Mach number dependent drag polar were obtained for six different aircraft types that are among the most used in today’s commercial air transportation. Automatic Dependent Surveillance–Broadcast (ADS-B) and Mode-S surveillance data were used for the analysis of the drag polars obtained for the climb profile. The cuckoo search algorithm (CSA) method was preferred for modeling. The algorithm estimated the calculated CD values for the simple drag polar and the Mach-based drag polar with margins of error between 1.78 x 10-6 and 5.59 x 10-6, and 4.04 x 10-8 and 4.29 x 10-5, respectively. Due to the accuracy of the proposed dataset, as indicated by the low mean squared error (MSE) values, it constitutes an important resource for subsequent aircraft performance studies.