Optimization of Fuel Consumption in Climb Trajectories using Genetic Algorithm Techniques

Abstract

The air transport industry is growing rapidly and there is increasing concern regarding the impact this will have on the environment. The European Commission has launched a Joint Technology Initiative, Clean Sky, to catalyze and consolidate efforts in the process of developing breakthrough technologies to address this problem and to reduce the impact of air transport on the environment. GATAC, which has been developed under Clean Sky, is a tool capable of generating optimal flight trajectories for multiple objectives including fuel consumption. This work makes use of GATAC to generate a number of economical climb trajectories for different aircraft weights for a specific case scenario, which are then modeled using curve-fitting techniques. The resulting functions are analyzed and integrated together in a way that the optimal climb trajectories of different aircraft weights could be determined without the need of running new optimizations. The purpose of this is two-fold, namely to reduce computational time, which is significant considering that GATAC makes use of genetic algorithms to support multi-objective, multi-disciplinary optimization studies; and to investigate the viability of such a technique to be applied in real-time online optimization in the next generation flight management system.