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Fuel burn prediction algorithm for cruise, constant speed and level flight segments

Published online by Cambridge University Press:  27 January 2016

B. D. Dancila ,
R. Botez  and
D. Labour
B. D. Dancila
Affiliation:
École de Technologie Supérieure, Montréal, Québec, Canada
R. Botez*
Affiliation:
École de Technologie Supérieure, Montréal, Québec, Canada
D. Labour
Affiliation:
CMC Electronics-Esterline, Saint-Laurent, Québec, Canada
*
[email protected]
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Abstract

This paper presents a new algorithm that predicts the quantity of fuel burned by an aircraft flying at a constant speed and altitude. It considers the continuous fuel burn rate variation with time caused by the gross weight (and centre of gravity position) modification due to the fuel burn process itself. The algorithm was developed for use by the Flight Management System (FMS) and employs the same aircraft performance data as the existing FMS fuel burn prediction algorithms. The new fuel burn method was developed for aircraft models that use the centre of gravity position as well as for models that do not consider the centre of gravity position. This algorithm was developed for normal flight conditions. Algorithm performances were evaluated for two aircraft models: one for models that use an aircraft’s centre of gravity position – a more complex and computing intensive method, and one for those that do not use the centre of gravity position. The validation data were generated based on the information produced on a CMC Electronics – Esterline FMS platform that used identical aircraft models and performance data for identical flight conditions.

Type
Research Article
Information
The Aeronautical Journal , Volume 117 , Issue 1191 , May 2013 , pp. 491 - 504
Copyright
Copyright © Royal Aeronautical Society 2013 

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References

1. Liden, S. The evolution of Flight Management Systems, Digital Avionics Systems Conference, 1994. 13th DASC., AIAA/IEEE, pp 157–169, 30 October – 3 November 1994. Online. <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=369487&isnumber=8448>..>Google Scholar
2. Herndon, A.A., Cramer, M. and Nicholson, T. Analysis of advanced flight management systems (FMS), flight management computer (FMC) field observations, trials; lateral and vertical path integration Digital Avionics Systems Conference, 2009. DASC ‘09. IEEE/AIAA 28th, pp.1.C.2-1-1.C.2-16, 23-29 October 2009. Online. <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5347572&i snumber=5347412>..>Google Scholar
3. Alonso-Portillo, I. and Atkins, E.M. Adaptive Trajectory Planning for Flight Management Systems, 2001, AAAI Technical Report SS-01-06. Online. <https://www.aaai.org/Papers/Symposia/Spring/2001/SS-01-06/SS01-06-001.pdf>..>Google Scholar
4. Wu, S.C., Duong, C.G., Koteskey, R.W. and Johnson, W.W. Designing a Flight Deck Predictive Weather Forecast Interface Supporting Trajectory-Based Operations, Ninth USA/Europe Air Traffic Management Research and Development Seminar (ATM2011) Berlin, Germany, 14-17 June 2011. Online. <http://www.atmseminar.org/seminarContent/seminar9/papers/151-Wu-Final-Paper-4-15-11.pdf>..>Google Scholar
5. Knapp, D.I., Jameson, T.E., Measure, E. and Butler, A. Optimized Flight Routing Based on Weather Impacts Grids, 13th Conference on Aviation, Range and Aerospace Meteorology, 88th Annual Meeting of the American Meteorological Society, 20-24 January 2008, New Orleans, LA, USA, Online. <http://ams.confex.com/ams/pdfpapers/132215.pdf>..>Google Scholar
6. Liden, S. Optimum cruise profiles in the presence of winds, Digital Avionics Systems Conference, 1992. Proceedings., IEEE/AIAA 11th, pp 254–261, 5-8 October 1992. Online. <http://ieeexplore.ieee. org/stamp/stamp.jsp?tp=&arnumber=282147&isnumber=6983>..>Google Scholar
7. Ardema, M.D. and Asuncion, B.C. Springer Optimization and Its Applications: Variational Analysis and Aerospace Engineering: Flight Path Optimization at Constant Altitude, 2009, 33, pp 21–32, New York, USA: Springer, 518 pages. Online. <http://www.springerlink.com/content/g731701lg3u2j576/fulltext.pdf>..>Google Scholar
8. Federal Aviation Administration, 2007, Aircraft Weight and Balance Handbook, 97pp, Online. <http://www.faa.gov/library/manuals/aircraft/media/FAA-H-8083-1A.pdf>..>Google Scholar
9. Butcher, J.C. The Numerical Analysis Of Ordinary Differential Equations: Runge-Kutta And General Linear Methods, 1987, New York, USA: Wiley-Interscience, pp 512.Google Scholar
10. Asselin, M. AIAA Education Series: An Introduction to Aircraft Performance, 1997, Reston, Virginia, USA: American Institute of Aeronautics and Astronautics, Inc, pp 339.Google Scholar
11. Botez, R. GPA-745: Introduction à l’avionique: notes de cours GPA-745. Bachelor and Master’s engineering programs. Montreal: Ecole de Technologie Superieure, multiple pagination, 2006, pp 394.Google Scholar
12. Botez, R. GPA-745: Introduction à l’avionique: notes de laboratoire GPA-745. Bachelor and Master’s engineering programs. Montreal: Ecole de Technologie Superieure, multiple pagination, 2006, pp 99.Google Scholar
13. Liden, S. Optimum 4D guidance for long flights, Digital Avionics Systems Conference, 1992. Proceedings., IEEE/AIAA 11th, pp 262–267, 5-8 October 1992. Online. <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp =&arnumber=282146&isnumber=6983http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=282 146&isnumber=6983>..>Google Scholar
14. Liden, S. Practical Considerations in Optimal Flight Management Computations, American Control Conference, pp 675–681, 19-21 June 1985, Online. <http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&amumber=4788700&isnumber=4788561&.Google Scholar