Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-26T11:16:45.943Z Has data issue: false hasContentIssue false
  • English
  • Français

Calculating block time and consumed fuel for an aircraft model

Published online by Cambridge University Press:  25 March 2021

F. de Lemos Open the ORCID record for F. de Lemos [Opens in a new window]  and
J. Woodward
F. de Lemos*
Affiliation:
Operational Reasearch Group School of Electronic Engineering and Computer Science Queen Mary university of London London UK
J. Woodward*
Affiliation:
Operational Reasearch Group School of Electronic Engineering and Computer Science Queen Mary university of London London UK
*
[email protected]
[email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

In this paper we present a novel approach to calculate Block Time and Fuel (BTF) consumed for an aircraft model during a flight. The BTF model computes the ground distance between the origin and destination airports, derives the flight’s cruise altitude and by integrating two institutional data sets calculates the duration and the fuel consumed for the whole of taxi-out, take-off, climb, cruise, descent, approach, landing and taxi-in phases. We use the French Association for Operational Research and Decision Support (ROADEF) 2009 Challenge flight rotation to sample our model. The statistical analysis of the results consisted of comparing BTF results for the block time and those from the ROADEF Challenge 2009 with the real ones retrieved from Flightaware® for the same origin and destination airports and aircraft model. Statistical results are reported for percentile and root mean square error, and we show that, using simple calculations, the BTF computational results for block time are in a lower percentile and have lower root mean square error than the block times used by the ROADEF 2009 Challenge. To compare the fuel consumed, we used the values for the real flights published in the literature review. We were able to verify a good fit between the BTF results and those values. Since the BTF model computational results are obtained within a few seconds, we also conclude that the BTF model is suited for flight planning and disruption recovery in commercial aviation.

Keywords

Travel timeTraffic data analysisOperation models
Type
Research Article
Information
The Aeronautical Journal , Volume 125 , Issue 1287 , May 2021 , pp. 847 - 878
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Neuman, F. and Kreindler, E., Minimum-fuel three-dimensional flight paths for jet transports, J. Guid. Control Dyn., 1985, 8 (5), pp 650–657.Google Scholar
Grimm, W., Well, K.H. and Oberle, H.J. Periodic control for minimum-fuel aircraft trajectories, J. Guid. Control Dyn., 1986, 9, (2), pp 169–174.Google Scholar
Betts, J.T. and Cramer, E.J. Application of direct transcription to commercial aircraft trajectory optimization, J. Guid. Control Dyn., 1995, 18, (1), pp 151–159.CrossRefGoogle Scholar
Hagelauer, P. and Mora-Camino, F. A soft dynamic programming approach for on-line aircraft 4D-trajectory optimization, Eur. J. Oper. Res., 1998, 107, (1), 87–95.Google Scholar
Franco, A., Rivas, D. and Valenzuela, A. Minimum-fuel cruise at constant altitude with fixed arrival time, J. Guid. Control Dyn., 2010, 33, (1), 280–285.CrossRefGoogle Scholar
Turgut, E.T. and Rosen, M.A. Relationship between fuel consumption and altitude for commercial aircraft during descent: preliminary assessment with a genetic algorithm, Aerosp. Sci. Technol., 2012, 17, (1), 65–73.CrossRefGoogle Scholar
Murrieta-Mendoza, A., Ruiz, H. and Botez, R.M. Vertical reference flight trajectory optimization with the particle swarm optimisation. In Modelling, Identification and Control, ACTAPRESS, 2017. doi: 10.2316/p.2017.848-032CrossRefGoogle Scholar
Hartjes, S., van Hellenberg Hubar, M.E.G. and Visser, H.G. Multiple-phase trajectory optimization for formation flight in civil aviation, CEAS Aeronaut. J., 2018, 10, (2), 453–462. doi: 10.1007/s13272-018-0329-9Google Scholar
Oruc, R. and Baklacioglu, T. Modelling of fuel flow-rate of commercial aircraft for the climbing flight using cuckoo search algorithm, Aircr. Eng. Aerosp. Technol., 2020, 92, (3), pp 495–501. doi: 10.1108/aeat-10-2019-0202CrossRefGoogle Scholar
EUROCONTROL. User Manual for the Base of Aircraft Data (BADA) Revision 3.14, 2014. http://www.eurocontrol.int/sites/default/files/field_tabs/content/documents/sesar/user-manual-bada-3-12.pdf.Google Scholar
Melby, P. and Mayer, R. Benefit potential of continuous climb and descent operations, The 26th Congress of ICAS and 8th AIAA ATIO, 2008, p 8920.Google Scholar
Robinson, III, J. and Kamgarpour, M. Benefits of continuous descent operations in high-density terminal airspace considering scheduling constraints, 10th AIAA Aviation Technology, Integration, and Operations (ATIO) Conference, 2010, p 9115.CrossRefGoogle Scholar
Knorr, D., Chen, X., Rose, M., Gulding, J., Enaud, P. and Hegendoerfer, H. Estimating ATM efficiency pools in the descent phase of flight, 9th USA/Europe Air Traffic Management Research and Development Seminar (ATM2011), vol. 5, 2011, pp 16–23.Google Scholar
Howell, D. and Dean, R. Have descents really become more efficient? USA/Europe Air Traffic Management R&D Seminar, Seattle, Washington, USA, 2017.Google Scholar
Khadilkar, H. and Balakrishnan, H. Estimation of aircraft taxi fuel burn using flight data recorder archives, Transp. Res. Part D Transport Environ., 2012, 17, (7), 532–537.Google Scholar
Ravizza, S., Atkin, J.A.D., Maathuis, M.H. and Burke, E.K. A combined statistical approach and ground movement model for improving taxi time estimations at airports, J. Oper. Res. Soc., 2013, 64, (9), pp 1347–1360.Google Scholar
Ravizza, S., Chen, J., Atkin, J.A.D., Stewart, P. and Burke, E.K. Aircraft taxi time prediction: comparisons and insights, Appl. Soft Comput., 2014, 14, pp 397–406.CrossRefGoogle Scholar
Chen, J., Weiszer, M., Locatelli, G., Ravizza, S., Atkin, J.A., Stewart, P. and Burke, E.K. Toward a more realistic, cost-effective, and greener ground movement through active routing: a multiobjective shortest path approach. IEEE Trans. Intell. Transp. Syst., 2016, 17, (12), pp 3524–3540. doi: 10.1109/tits.2016.2587619CrossRefGoogle Scholar
Gardi, A., Sabatini, R. and Ramasamy, S. Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context, Prog. Aerosp. Sci., 2016, 83, pp 1–36. doi: 10.1016/j.paerosci.2015.11.006CrossRefGoogle Scholar
Enea, G., Fricke, H., Paglione, M. and Bronsvoort, J. Australia Airservices, Melbourne, Almira Australia, Ramadani, Christian Sei, and Judith Rosenow. Fuel burn estimation modeling for ATM benchmark applications perspectives from an international collaboration, July 2017.Google Scholar
Glaser-Opitz, H., Labun, J., Budajová, K. and Glaser-Opitz, L. Descent trajectory modelling for the landing system prototype, Transport, 2020, 35 (2), pp 133–142. doi: 10.3846/transport.2020.12231.Google Scholar
Pagoni, I. and Psaraki-Kalouptsidi, V. Calculation of aircraft fuel consumption and CO2 emissions based on path profile estimation by clustering and registration, Transp. Res. Part D Transport Environ., 2017, 54, pp 172–190.CrossRefGoogle Scholar
Flightaware Flight Track Log AFR1148. Flight Track Log - AFR1148, 2019 https://uk.flightaware.com/live/flight/AFR1148/history/20191023/0520Z/LFPG/LEBL/tracklog.Google Scholar
Alam, S., Tang, J., Lokan, C.J. and Abbass, H.A. An assessment of BADA fuel flow methodologies for in-trail procedure evaluation. Defence & Security Applications Research Centre, University of New South Wales, Australian Defence Force Academy, Canberra, Australia, 2009.Google Scholar
Flightaware Flight AFR1148. Flight AFR1148, 2019 https://uk.flightaware.com/live/flight/AFR1148/history/20191023/0520Z/LFPG/LEBL.Google Scholar
Flightaware. Flight Track Log, 2019. https://uk.flightaware.com/.Google Scholar