The current lack of efficiency in the use of airspace, enforced by the economic crisis an the increasing competitiveness among air transport companies are drivers for a renewed interest for the application of optimization techniques to find answers to overcame current inefficiencies.The main objective of the present paper is to assess and compare different optimal aircraft trajectories techniques applied to the minimum fuel cruise problem at constant altitude and course with fixed arrival time, International Standard Atmosphere and without wind. Four trajectory optimization methods have been used: Hermite-Simpson , 5th degree Gauss-Lobatto and Radau pseudospectral collocation methods and the singular arc solution.Hermite-Simpson and 5th degree methods have been programmed in Ampl modeling language with an IPOPT solver and Radau pseudospectral method using gpops matlab tool with SNOPT solver. 5th degree Gauss-Lobatto collocation method gives the less fuel consumption solution followed by Radau pseudospectral, Hermite-Simpson and singular arc. In considering the program execution time, Hermite-Simpson collocation method is the fastest method followed by 5th degree and Radau pseudospectral. Also, taking into account the time for developing the program code the Radau pseudospectral is the most user friendly. Moreover, it has been observed that increasing the sample points in the HermiteSimpson and 5th degree, the solution converge to the minimum fuel consumption solution. On the other hand, gpops does not show much sensitivity to the number of sample points.
Aircraft Operators Companies (AOCs) are always willing to keep the cost of a flight as low as possible. These costs could be modelled using a function of the fuel consumption, time of flight and fixed cost (over flight cost, maintenance, etc.). These are strongly dependant on the atmospheric conditions, the presence of winds and the aircraft performance. For this reason, much research effort is being put in the development of numerical and graphical techniques for defining the optimal trajectory. This paper presents a different approach to accommodate AOCs preferences, adding value to their activities, through the development of a tool, called aircraft trajectory simulator. This tool is able to simulate the actual flight of an aircraft with the constraints imposed. The simulator is based on a point mass model of the aircraft.The aim of this paper is to evaluate 3DoF aircraft model errors with BADA data through real data from Flight Data Recorder FDR. Therefore, to validate the proposed simulation tool a comparative analysis of the state variables vector is made between an actual flight and the same flight using the simulator. Finally, an example of a cruise phase is presented, where a conventional levelled flight is compared with a continuous climb flight. The comparison results show the potential benefits of following user-preferred routes for commercial flights.
A novel study is presented aiming at characterizing and illustrating potential enhancements in flight planning predictability due to the effects of wind uncertainty. A robust optimal control methodology is employed to calculate robust flight plans. Wind uncertainty is retrieved out of Ensemble Probabilistic Forecasts. Different wind approximation functions are compared, typifying errors, and illustrating its importance for accurate solving of the robust optimal control problem. A set of key performance indicators is defined for the quantification of uncertainty in terms of flight time and fuel consumption. Two different case studies are presented and discussed. The first one is based on a representative sample of the whole 2016 year for a single origin-destination and a forecast time step of 6 hours. As for the second, we select the most uncertain day together with a multiorigin-destination set of flights with forecast time steps up to 2 days.
The existence of significant uncertainties in the models and systems required for trajectory prediction represent a major challenge for Trajectory-Based Operations concept. Weather can be considered as one of the most relevant sources of uncertainty. Understanding and managing the impact of these uncertainties is necessary in order to increase the predictability of the ATM system. We present preliminary results on robust trajectory planning in which weather is assumed to be the unique source of uncertainty. State-of-the-art forecasts from Ensemble Prediction Systems are used as input data for the wind field and to calculate convective risk. The term convective area is defined here as an area within which individual convective storms may develop, i.e., a necessary (though not sufficient) condition. An ad-hoc robust optimal control methodology is presented. A set of Pareto-optimal trajectories is obtained for different preferences between predictability, convective risk and average efficiency. 2020 research and innovation programme. Consortium members are UNI-VERSITY OF SEVILLE (Coordinator),
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