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.

The current Flight Management System, CMA-9000, from CMC Electronics -Esterline, does not include a cruise optimization. In the presence of winds, the aircraft fuel consumption is highly affected. If the aircraft experiments head winds, the consumption will increase, and the consumption will decrease in the case of tail winds. The cruise phase is analyzed using genetic algorithms to obtain the maximal optimization possible in the least calculation time. In this article, an algorithm will be defined, that will be capable of selecting an alternative trajectory to take advantage of tail winds in the flight path, and to avoid as much as possible the presence of head winds, to reduce fuel burn. NomenclatureATC = Air Traffic Control FMS = Flight Management System GA = genetic algorithm IAS = indicated airspeed PDB = performance database TOC = top of climb TOD = top of descent

In order to reduce fuel savings in a given flight the vertical navigation profile in terms of speed and altitude that provides the most economical flight has to be found. An algorithm was developed using an aircraft performance database to determine the optimal vertical flight profile considering a take-off weight, flight distance, step climb and weather conditions. This algorithm is based on linear interpolations of the performance tables using the Lagrange method. The algorithm according to departure date and coordinates, download the latest available forecast from environment Canada website and calculate the optimal taking into account the effects of wind, pressure and temperature. NomenclatureCI = Cost index FL = Flight level FMS = Flight Management System GARDN = Green Aviation Research & Development Network ISA = International Standard Atmosphere KIAS = Knots Indicated Airspeed LARCASE = Laboratory Research Laboratory in Active Controls, Avionics Controls, Avionics and Aeroservoelasticity. NFZ = No fly zones PDB = Performance database TOC = Top of climb TOD = Top of descent UTC Coordinated Universal Time VNAV = Vertical navigation

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