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Advanced Engine Off Navigation

Periodic Reporting for period 1 - AEON (Advanced Engine Off Navigation)

Reporting period: 2020-11-01 to 2021-10-31

Taxibots, E-Taxi systems, single engine taxiing are some of the technologies under investigation by partners in the SESAR JU AEON project to reduce significantly CO2 emissions caused by aircraft taxiing at airports.
Funded within the framework of Horizon 2020, the Advanced Engine Off Navigation (AEON) project aims to define a concept of operations for engine-off taxiing techniques, making use of novel technologies that are coming onto the market, such as:
• Non-autonomous taxiing, such as TaxiBots, a hybrid towing vehicle which, unlike the normal pushback trucks, can tow full aircraft to near the start of the runway, without the aircraft having to start its engines. This is expected to reduce fuel consumption during taxiing by 50% to 85%.
• Autonomous taxiing like E-Taxi system, which relies on electric motors embedded in landing gear to allow planes to push back and taxi without their jet engines running - saving fuel, curbing emissions and ending last-minute delays while waiting for airport tugs. This is expected to imply a reduction in fuel costs of around 4% of the overall consumption, considering a 50% taxi fuel saving and up to 85% of ground operations costs savings considering other benefits like pushback costs, brake wear...
• Single engine taxiing, which involves using only half the number of engines installed to generate the energy needed for taxiing, reducing taxi fuel consumptions by 20%.
These fuel savings are coming along with reduced noise and CO2/NOx emissions.
Bringing together knowledge and expertise from research partners ENAC, Deep Blue and TU Delft, the project will work closely with airports, airlines and manufacturers on developing the following:
• Overall aircraft engine-off navigation concept of operations, detailing how the three eco-friendly solutions above may combine in the airport surface management process both at strategical and tactical level in order to minimise fuel consumption and emissions without impacting arrival and departure flight schedules;
• Business model to help airports and/or airlines evaluate their benefits in the implementing these technologies;
• Real-time evaluation of environmental indicators to support decision-making, conflict free routing for all vehicles, reallocation of techniques to adapt to in real time.
The project will aim to ensure that their approach can be integrated in to airport collaborative decision-making tools.
The research is very much in line with the SESAR JU’s goal of delivering solutions to make aviation smarter and more sustainable in support of the Commission’s strategy in this area.
This project has received funding from the SESAR Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No 892928
The main objective of the project is to produce a concept of operations for engine-off taxiing techniques. In this first period, an initial version has been produced and presented to the advisory board. In preparation for this document, a state of the art has been performed and delivered. In addition, several interviews with different stakeholders (see Intermediate Dissemination Report deliverable D6.1) have helped getting a clear understanding of the different constraints and information needed by each other. Based on that, the objectives of the different sub parts of the solution have been clarified:
• Tugs Fleet management algorithm: It will perform two tasks. First one is to determine the minimum number of tugs needed to handle a typical day of traffic. The goal is to help dimension the fleet for a given airport. The second task is to allocate tugs to aircraft to support the fleet manager during operations, it will be able to reconfigure quickly to take into account operational events. The first task has actually been implemented and need to be integrated and validated on the final solution. The second task is under development.
• Routing suggestion algorithm: The routing suggestion provided on demand to the ATCO or the tug driver will include a speed profile to help smooth traffic and avoid stop and goes. The engine off taxiing operations also requires more detailed information concerning the aircraft unload location for non-autonomous taxiing and ideal time to start-up engines. A first version of the multi-agent system is available. Further discussions are on going about the criteria to be optimised in the suggestions (taxi time, length…)
• Although several existing HMIs would be impacted by the introduction of engine off taxiing techniques, the design and prototyping activities will focus on A-SMGCS, aircraft pilot HMI (moving map or EFB) and a new tool for the tugs fleet manager. New features have been implemented in the A-SMGCS prototype to represent the different taxi techniques and allow route editing. The design work for the fleet manager is started, a preliminary design is available. Finally, a basic moving prototype has been developed from the A-SMGCS version.
In the meantime, the integration of the different tools in ENAC facilities has made some progress. First a dedicated tool has been developed to generate all the data needed for the different modules to simulate an airport platform. In this manner every module will share the same information, avoiding integration issues. The tool used open data to generate any airport data, not only Roissy CDG and Amsterdam Schiphol as needed for the project. The simulation engine is also to generate the dynamics corresponding to the different engine off taxiing techniques. Finally, the demo setup is planned to be directly installed in Roissy CDG premises so that it will be easier to show it to operational staff and gather feedback.
Cost Benefit Analysis has also been started with an analysis of the different existing techniques their comparison and potentially a proposition of mitigation solution to get a better cost benefit ratio.
Expected results:
• Initial concept of operations refined after live demonstrations with operational staff
• Design and prototyping of A-SMGCS functions, cockpit view for routing (EFB) and tugs fleet manager
• Scientific publications on algorithms and HMI design