KnE Engineering

ISSN: 2518-6841

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Optimal Fuel Saving in 4D Waypoint Networks

Published date: Jun 02 2020

Journal Title: KnE Engineering

Issue title: International Congress on Engineering — Engineering for Evolution

Pages: 500–513

DOI: 10.18502/keg.v5i6.7065

Authors:

Kawser Ahmed - kawser.ah91@gmail.com

Milca de Freitas Coelho

Kouamana Bousson

Abstract:

The purpose of this work is to develop a trajectory optimization method that generates a fuel optimal trajectory from a predefined 4D waypoint networks, where the arrival time is specified for each waypoint in the network. A single source shortest path algorithm is presented to generate the optimal flight trajectory that minimizes fuel burn. Generating such trajectories enables the airlines to cope with increasing fuel costs and to reduce aviation induced climate change, as emission is directly related to the amount of fuel burn. Two case studies were considered and the simulation results showed that flying a fuel optimal trajectory based on the proposed algorithm leads to a reduction of average fuel consumption on international flights by 2-4% compared with the conventional trip fuel.

Keywords: Fuel saving, Cost index, 4D trajectory optimization, Waypoint network, Dijkstra’s algorithm

References:

[1] ICAO. ICAO Environmental Report: Aviation and Climate change. ICAO, 2013.

[2] Robenson B. Fuel Conservation Strategies: Cost Index Explained. Boeing, 2007, pp.26-28.

[3] Roberson W. and Johns J. A. Fuel Conservation strategies: Takeoff and Climb. Boeing, 2008, pp.25-28.

[4] Roberson W. and Johns J. A. Fuel Conservation Strategies: Descent and Approach. Boeing, 2008, pp. 25-28.

[5] Bryson A. E and Ho Y. C. Applied Optimal Control: Optimization, Estimation and, Control. Taylor & Francis, New York, 1975.

[6] Betts, J.T.: “Survey of numerical methods for trajectory optimization” Journal of Guidance, Control, and Dynamics, 1998, pp. 193-207.

[7] Pontryagin, L.S., Boltyanskii V.G., Gamkrelidze R.V., Mishchenko E.F. The Mathematical Theory of Optimal Processes. Wiley-Interscience, New-York, 1962.

[8] Von Stryk, O. and Bulirsch R.: “Direct and indirect methods for trajectory optimization” Annals of Operations Research, 37, 1992, pp. 357-373.

[9] Hull, D.G.: “Conversion of Optimal Control Problems into Parameter Optimization Problems” Journal of Guidance, Control, and Dynamics, 1997, pp. 57-60.

[10] Schwartz, A. and Polak E.: “Consistent approximations for Optimal Control Problems Based on Runge- Kutta Integration” SIAM Journal on Control and optimization, vol.34, No.4, 1996, pp. 1235-1269.

[11] Hargraves, C.R. and Paris S.W.: “Direct Trajectory Optimization Using Nonlinear Programming and Collocation” Journal of Guidance, Control and Dynamics, vol. 10, No.4, 1987, pp. 338-342.

[12] Bousson, K. Chebyshev pseudospectral trajectory optimization of differential inclusion models. SAE World Aviation Congress, Montreal, Canada, paper no. 2003-01-3044, 2003.

[13] Fahroo, F. and Ross I.M.: “Direct trajectory optimization by a Chebyshev pseudospectral method”Journal of Guidance, Control, and Dynamics, 2002, pp. 160-166.

[14] Bousson K. and Machado P.: ”4D Flight Trajectory Generation and Tracking for Waypoint- Based Aerial Navigation” WSEAS transactions on system and control, Vol 8, No 3, July 2013, pp 105-119.

[15] Bousson K, and Gameiro T. A.: ” A Quintic Spline Approach to 4D Trajectory Generation for Unmanned Aerial Vehicles” International Review of Aerospace Engineering (IREASE), Vol 8, No 1, 2015.

[16] Boukraa D., Bestaoui Y. and Azouz N.: ”Three Dimensional Trajectory Generation for an Autonomous Plane” International Review of Aerospace Engineering (IREASE), Vol 2, No 4, 2014.

[17] Ahmed K, and Bousson K.: ” Generating Time Optimal Trajectory from Predefined 4D waypoint Networks” International Review of Aerospace Engineering (IREASE), Vol 10, No 4, 2017.

[18] Seemkooei A. A.: ”Comparison of different algorithm to transform geocentric to geodetic coordinates”Survey Review 36, 286 October 2002. pp. 627-632.

[19] Aircraft Performance Summary Tables for the Base of Aircraft Data (BADA). Eurocontrol Experimental Centre, Revision 3.4, June 2002.

[20] User Manual for the Base of Aircraft Data (BADA). Eurocontrol Experimental Centre, Revision 3.9, April 2011.

[21] Cormen T. H, Leiserson C. E, Rivest R. L and Stein C. Introduction to algorithms. London, England: The MIT Press, 2009, pp. 658-659.

[22] Hart C. Graph Theory Topics in Computer Networking. 2013, pp 13-20.

[23] Dasgupta S., Papadimitriou C. H. and Vazirani U. V. Algorithms. McGraw-Hill, New York, July 18, 2006, pp. 112-118.

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