The advent of high-bandwidth data link radios, airborne broadband internet service, and Electronic Flight Bags (EFB) has enabled the development of low-cost decision support tools that improve operating efficiency. Government laboratories, private companies, and academia are developing these tools as software applications installed on EFBs and computing resources in airline dispatch centers. While these tools achieve small improvements in efficiency on a per flight basis, the cost savings is significant over the service life of an airplane and substantial for a fleet of airplanes. Considering the many unpredictable and uncontrolled variables that affect fuel burn and operating cost, the problem of quantifying the benefit over a specified service interval becomes a fundamental challenge. The basis of comparison that determines the value of a technology in today's market is very subjective. A consensus-based industry standard for measuring the monetary benefit of optimal guidance and control has not been established. GE has developed new methods for computing cost-optimal control and state trajectories for air transports and an approach to quantify the monetary benefit an operator can expect relative to a baseline control system. This method yields a fair comparison given the nature of uncontrolled variables that affect fuel burn and non-deterministic control constraints due to air traffic and weather which limit the crew's discretionary control of the airplane. This paper describes one of GE's flight path optimization applications that eliminates the simplifying assumptions applied to legacy path construction methods to improve operational efficiency. The benefits of this new approach have been assessed using a high-fidelity, physics-based computer simulation of various aircraft types. A novel approach to quantify the benefit-compares the cost of GE's state-of-the-art Flight Management System (FMS) augmented by GE's decision support tool with the cost realized by GE's FMS operating without the benefit of decision support. Weather data from NOAA's Rapid Refresh (RAP) system are used to simulate flights on different calendar days. Comparing two simulated flights removes uncertainties due to aircraft modelling, weather, and ATM routing. The results of the Monte Carlo study are characterized statistically to quantify the cost savings.


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    Titel :

    Quantifying operating cost reduction from aircraft performance optimization


    Beteiligte:
    Lax, David (Autor:in) / Darnell, Mark (Autor:in) / O'Keefe, Owen (Autor:in) / Rhone, Brandon (Autor:in) / Visser, Nick (Autor:in) / Ghaemi, Reza (Autor:in) / Westervelt, Eric R. (Autor:in)


    Erscheinungsdatum :

    2018-04-01


    Format / Umfang :

    927631 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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