Fuel consumption is one of the major considerations for both the impact of aviation in the environment and the cost of operations. This paper assesses the accuracy of a method capable of producing aircraft fuel estimates based on their 4D trajectory timestamps and the weather forecast. Fuel consumption estimates generated for 2448 descents are compared with the flight data recorder (FDR) values provided by the airline. Fuel consumption is estimated by taking the 4D trajectory from two different sources: the FDR system itself and surveillance radar tracks. In both cases, the Base of Aircraft Data (BADA) and a model that fits manufacturers’ performance data to polynomial functions are used to represent aircraft performance. Results obtained with the latter show that fuel usage could be estimated with an accuracy of 16 kg (4.8%) using the 4D trajectory as reported by the FDR system and 28 kg (7.8%) using surveillance radar observations. It is also observed that the BADA 3.6 model underestimates the fuel consumption, illustrating the need for an improved performance model in the terminal manoeuvring area. This method could be the cornerstone for the calculation of advanced performance indicators to measure flight efficiency (and environmental impact) in post-operational assessments, since it enables the estimation of the full state vector of an aircraft, including variables that are not explicitly included in the surveillance data (such the fuel, thrust, etc.).
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
This is the net price. Taxes to be calculated in checkout.
Airbus PEP software provides a high degree of precision in the certified aircraft performance data and uses specific flight management system (FMS) algorithms for the computations.
SESAR Joint Undertaking: European ATM Master Plan. The roadmap for delivering high performing aviation for Europe. Brussels (Belgium), Tech. Rep., (2015)
Prats, X., Dalmau, R., Barrado, C.: Identifying the sources of flight inefficiency from historical aircraft trajectories. A set of distance- and fuel-based performance indicators for post-operational analysis, In: Proceedings of the 13th USA/Europe Air Traffic Management Research and Development Seminar. Vienna (Austria): Eurocontrol and FAA, (2019)
Jin, L., Cao, Y., Sun, D.: Investigation of potential fuel savings due to continuous-descent approach. J. Aircr. 50(3), 807–816 (2013)
Thompson, T., Miller, B., Murphy, C., Augustine, S., White, T., Souihi, S.: Environmental impacts of continuous-descent operations in Paris and New York regions. Isolation of ATM/airspace effects and comparison of models, In: Proceedings of the Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013), Chicago, Illinois (USA), (2013)
Dalmau, R., Prats, X.: Fuel and time savings by flying continuous cruise climbs: estimating the benefit pools for maximum range operations. Transport. Res. Part D Transport Environ. 35, 62–71 (2015)
Peeters, S., Koelman, H., Koelle, R., Galaviz-Schomisch, R., Guldingand, J., Meekma, M.: Towards a common analysis of vertical flight efficiency, In: Proceedings of the Integrated Communications Navigation and Surveillance (ICNS). IEEE, (2016)
Knorr, D., Chen, X., Rose, M., Gulding, J., Enaud, P., Hegendoerfer, H.: Estimating atm efficiency pools in the descent phase of flight. Potential savings in both time and fuel, In: Proceedings of the 9th USA/Europe Air Traffic Management Research and Development Seminar. Berlin (Germany): Eurocontrol and FAA, (2011)
C. I. Alternative Emissions Task Group: guidance on the use of LTO emissions certification data for the assessment of operational impacts, ICAO committee on aviation environmental protection (CAEP) Working Group 3, (2004)
Patterson, J., Noel, G., Senzig, D., Roof, C., Fleming, G.G.: Analysis of ICAO departure profile using real-time cockpit flight data recorder information, In: Transportation Research Board 87th Annual Meeting, (2008)
Patterson, J., Noel, G.J., Senzig, D.A., Roof, C.J., Fleming, G.G.: Analysis of departure and arrival profiles using real-time aircraft data. J. Aircr. 46(4), 1094–1103 (2009)
Senzig, D.A., Fleming, G.G.: Fuel consumption modeling in support of atm environmental decision-making, In: 8th USA/Europe Air Traffic Management Research and Development Seminar, (2009)
Senzig, D.: Terminal area fuel burn analyses for environmental models, Ops SC Atlanta Meeting., (2008)
Chatterji, G.B.: Fuel burn estimation using real track data, In: 11th AIAA ATIO conference, AIAA centennial of naval aviation forum, (2012)
Oaks, R.D., Paglione, M.: Prototype implementation and concept validation of a 4-d trajectory fuel burn model application, In: AIAA guidance, navigation, and control conference, (2010)
Eurocontrol: user manual for the base of aircraft data (BADA). Revision 3.6, Eurocontrol, Bretigny (France), (2004), aCE-C-E2
ICAO: Manual of the ICAO standard atmosphere: extended to 80 kilometres (262500 feet), International Civil Aviation Organization, Montreal, Canada, Tech. Rep., (1993)
Senzig, D.A., Fleming, G.G., Iovinelli, R.J.: Modeling of terminal-area airplane fuel consumption. J. Aircr. 46(4), 1089–1093 (2009)
Kaiser, M., Schultz, M., Fricke, H.: Enhanced jet performance model for high precision 4D flight path prediction, In: Proceedings of the 1st international conference on application and theory of automation in command and control systems (ATACCS), pp. 33–40 (2011)
Air force test pilot school, Edwards AFB, CA, Cruise performance theory, In: Performance phase, vol. 1, ch. 11 (1993)
Dalmau, R., Pérez-Batlle, M., Prats, X.: Estimation and prediction of weather variables from surveillance data using spatio-temporal kriging, In: Proceedings of the 36th digital avionics systems conference (DASC). Saint Petersburg, FL: IEEE/AIAA, (2017)
Haan, S.D.: Quality assessment of high resolution wind and temperature observation from ModeS. The Royal Netherlands Meteorological Institute (KNMI), The Netherlands (2010)
Kalman, R.E.: A new approach to linear filtering and prediction problems. Trans. ASME J. Basic Eng. 82, 35–45 (1960)
Gray, J., Murray, W.: A derivation of an analytic expression for the tracking index for the alpha-beta-gamma filter. IEEE Trans. Aerosp. Electron. Syst. 29(3), 1064–1065 (1993)
de Boor, C.: A practical guide to splines. Applied mathematical sciences. Springer, New York (2001)
Chartrand, R.: Numerical differentiation of noisy, nonsmooth data. Los Alamos National Laboratory, Los Alamos (2005)
Savitzky, A., Golay, M.J.E.: Smoothing and differentiation of data by simplified least squares procedures. Anal. Chem. 36(8), 1627–1639 (1964)
Price Elliott, M.: A methodology for determining aircraft fuel burn using air traffic control radar data, Master’s thesis, Georgia Institute of Technology, (2011)
Alligier, R., Gianazza, D., Ghasemi Hamed, M., Durand, N.: Comparison of two ground-based mass estimation methods on real data, In: ICRAT 2014, 6th International Conference on Research in Air Transportation, Istanbul, Turkey, (2014)
Alligier, R., Gianazza, D., Durand, N.: Machine learning and mass estimation methods for ground-based aircraft climb prediction. IEEE Trans. Intell. Transport. Syst. 16, 3138–3149 (2015)
SESAR Joint Undertaking: SESAR 2020 Transition Performance Framework, Tech. Rep., deliverable D108. Version 00.02.00 (2016)
APACHE Consortium: Final project results report, Tech. Rep., Jul 2018, deliverable D1.2. Version 00.02.00
INTUIT Consortium: Final project results report, Tech. Rep., Jun 2018, deliverable D1.3. Version 00.01.00
AURORA Consortium: Final project results report, Tech. Rep., Mar 2018, deliverable D1.3. Version 00.01.01
The authors would like to thank Airbus Industries for the use of PEP (Performance Engineers Program) suite, which allowed to undertake realistic aircraft performances simulations. The authors also acknowledge the contributions of Ms. Angela Nuic from EUROCONTROL and the BADA team, which offered access to performance models for this validation exercise.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Dalmau, R., Prats, X., Ramonjoan, A. et al. Estimating fuel consumption from radar tracks: a validation exercise using FDR and radar tracks from descent trajectories. CEAS Aeronaut J 11, 355–365 (2020). https://doi.org/10.1007/s13272-020-00441-2
- Fuel consumption
- Aircraft performance
- Environmental impact
- Surveillance data
- Parameters estimation