Optimal aircraft trajectory planning based on high-resolution actual weather data

The aim of the graduation thesis Optimal Aircraft Trajectory Planning based on High-resolution Actual Weather Data is to enhance the aircraft flight plans in terms of wind-optimal speed and altitude scheduling with the utilization of the spatial and temporal high-resolution wind and temperature data. It is tried to utilize the weather information and the optimization process from the viewpoint of ground-based aircraft trajectory prediction. To achieve the objectives of this thesis firstly, a bunch of the aircraft flight plans is precisely simulated using the BADA4-based high fidelity trajectory predictor and compared with the actual flown data retrieved from the respective QAR source to observe how closely the planned trajectories were followed in actual flights. Secondly, with use of the wind forecast in the flight plan, aircraft trajectories are optimized respectively and the potential fuel and/or time-saving are observed. Thirdly, With the investigation of the impact of the wind uncertainty, the aircraft trajectories are optimized utilizing the actual HRES wind data from QAR and the change in fuel consumption and elapsed time are observed. Next, utilizing the cost index adjustment algorithm as a Fine tuning process for the wind-optimal trajectories, a novel process is performed as a re-optimization process to define the wind-optimal CI optimized according to the wind data. The proposed dynamic wind-optimal CIs are cumulatively equal to the CI defined by the airlines. Finally, a detailed analysis over a set of 400 long-haul flights is done to show the impact of the wind uncertainty over the trip time and trip fuel. Also, the cumulative potential fuel and/or time savings for multiple case studies are illustrated in details along with the aggregate results. It is also emphasized that wind speed gradient with altitude should be considered as well. In result, it is seen that cruise Mach number and cruise altitude together are key parameters for fuel consumption under the wind effect. Hence, the uncertainty in the wind may cause flying at non-optimal conditions. Recovering this uncertainty and planning the best trajectory in strategical level could be advantageous for airline operations. Applying the novel idea of wind-optimal CI to the flown planned flights using high fidelity trajectory predictor, a fuel-saving purely related to the DCI method is being achieved. At this stage of the work, a short duration flight with a low number of waypoints is considered, which resulted in a fuel saving with maintaining the time of arrival. The analysis is done according to the operational flight plan and actual flight data. It is aimed to apply this method to different flights with various conditions to generalize and verify the proposed tool. The fuel savings achieved by the methodology described in this paper complies with the expected outlook by SESAR (300 - 500 kg on average). The wind uncertainty affects the strategic planning of flights. This study showed the differences between forecast and actual wind information leads to having different fuel consumptions. Considering how the actual wind deviates from the planned ones, fuel savings can be achieved by the methodology described in this paper. Therefore, having access to the accurate wind information, the approach in this work can be utilized to revise the strategic fight planning. The results show that this work is more suitable for applying to the long-haul flights. This graduation thesis is composed of six chapters, each of them dealing with different aspect of satisfying the objective of the thesis. Chapter one is introductory and describes the purpose of the thesis, the relevant works that have been done before and clearly defines the contribution of this work. The literature review is divided into three subsections; wind forecast and data assimilation, trajectory optimization and dynamic cost index to give detailed information about each part of this thesis. Chapter two is dedicated to the background information needed for this work and consists of three parts. part one analyzes the impact of the wind uncertainty over the aircraft trajectory and the along-track difference is defined as the metric for this analysis. part two focuses on the fundamental background information about the cruise phase of the flight and describes in details the cruise flight formulation, which is of the interest of this work. Part three is dedicated to the fuel-efficient trajectory optimization, divided into speed and altitude optimization. The speed optimization, which is the main part of this thesis is described in details with three different methods as Maximum Range Cruise (MRC), Long Range Cruise (LRC) and Economy/Cost Index (CI). In the end, the process of the optimal altitude generation is described in details. Chapter three deals with the data resources and data parsing process for this work. The acquired flight plans from Turkish Airlines are explained in details, then the actual flight data from the aircraft Quick Access Recorder (QAR) is described. In the end, the weather forecast, NOAA GFS data, are visualized and described. Chapter four focuses on the aircraft trajectory prediction tool and defines the process step by step. Firstly, it is described why the Eurocontrol BADA 4 is chosen as the core aircraft model of this work by comparing the Eurocontrol BADA 3 and BADA 4 functions such as aerodynamics, Engine thrust and fuel consumption model. Then, the aircraft motion modeling is defined as explaining the governing equations in details followed by modeling the aircraft dynamics as a point-mass model as in BADA 4. Chapter five is concerned with the methodology used in this work. Firstly, a detailed description of the proposed work and method is defined showing the workflow of this thesis, the inputs, processes, and the desired output. Then, the first core block, which is cost index adjustment is formulated and described in details. Speed optimization is also described in details defining the aircraft performance limits and how the solution of the optimization formula for the speed scheduling the optimal solution. Afterward, nine actual flight plans are simulated with proposed methods to show the performance of the developed trajectory predictor, which is desired and acceptable. Conclusions are drawn in chapter six along with the simulation results. Firstly, it is tried to show the exact impact of the wind uncertainty, the difference between the actual wind and the forecast wind, over the trip time and trip fuel over 400 long-haul flights. Then the simulation results of utilizing HRES wind data against low-resolution one is shown and discussed followed by the description of the generation of the artificial flight plans and analysis of speed schedule. Also, the simulation results of the CI adjustment is illustrated and discussed.