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New Adaptive Algorithm Development for Monitoring Aircraft Performance and Improving Flight Management System Predictions

2019; American Institute of Aeronautics and Astronautics; Volume: 17; Issue: 2 Linguagem: Inglês

10.2514/1.i010748

2327-3097

Georges Ghazi, Benoît Gérardin, Magali Gelhaye, Ruxandra Mihaela Botez,

Aerospace and Aviation Technology

To compute the most efficient route that the aircraft has to fly, the flight management system (FMS) needs a mathematical representation of the aircraft performance. However, after several years of operation, various factors can degrade the overall performance of the aircraft. Such degradation can affect the reliability of the aircraft model, and the crew would lose confidence in the fuel planning estimated by the FMS. This paper presents the results of a study in which a new adaptive algorithm is proposed for continuously updating the FMS performance model using cruise flight data. The proposed algorithm combines aircraft performance monitoring techniques with adaptive lookup tables to model the aerodynamic characteristics of the aircraft. The methodology was applied to the well-known Cessna Citation X business aircraft, for which a research aircraft flight simulator was available. The development of this methodology was accomplished by creating an initial performance model, adapting it using flight data in cruise, and finally comparing its prediction with a series of flight data collected with the flight simulator. Results have shown that the proposed methodology was able to reduce fuel flow prediction mean errors by about 5%, whereas the standard deviation was reduced by a factor of 3.4.