Commercial Airline Speed Optimization Strategies for Reduced Cruise Fuel Consumption

Jensen, Luke; Hansman, R. John; Venuti, Joseph; Reynolds, Tom

doi:10.2514/6.2013-4289

Cited by 40 publications

(15 citation statements)

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“…Flight trajectory planning has been identified as a means to reduce fuel consumption and optimize flight costs and management. This expectation has been validated by Jenset et al [10][11][12] , whose studies showed that aircraft do not always fly at their optimal speeds and altitudes. Developing algorithms that optimize the flight reference trajectory is thus a realistic approach to reducing fuel consumption.…”

Section: Introductionmentioning

confidence: 65%

New Search Space Reduction Algorithm for Vertical Reference Trajectory Optimization

Murrieta-Mendoza¹,

Gagné²,

Mihaela³

2016

INCAS BULLETIN

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Section: Introductionmentioning

confidence: 65%

New Search Space Reduction Algorithm for Vertical Reference Trajectory Optimization

Murrieta-Mendoza¹,

Gagné²,

Mihaela³

2016

INCAS BULLETIN

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“…The tool will implement the altitude and speed optimization methods used in previous studies 2, 3,4 to provide additional cruise efficiency information to the flight crew. The additional information provided to the pilot can be used to make tactical decisions on aircraft altitude and speed.…”

Section: Objectivementioning

confidence: 99%

“…A diagram of the data sources and the software architecture is shown in Figure 4. American Institute of Aeronautics and Astronautics Given the required input data, the current and future fuel efficiency environment is calculated using an altitude optimization method developed in previous studies 2, 3,4 .…”

Section: Amentioning

confidence: 99%

Cruise Altitude and Speed Optimization Implemented in a Pilot Decision Support Tool

Folse

Tran

Jensen

et al. 2016

16th AIAA Aviation Technology, Integration, and Operations Conference

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A speed and altitude optimization application for Electronic Flight Bag (EFB) platforms has been developed that integrates an aircraft's planned route, weight, speed, and weather conditions to compute the fuel savings of altered cruise trajectories. Improved speed and altitude efficiency awareness has the potential to impact pilot route planning, air traffic control requests, and tactical decisionmaking. With current cockpit technology, pilots are not always presented with sufficient information to improve trajectory efficiency with respect to altitude and speed given operational constraints. In order to evaluate the effects of this additional information, a scenario-based human-in-the-loop usability study is performed for the proposed EFB application. Preliminary results from the study provide insight on the effects of improved speed and altitude efficiency information on pilot workload and decision-making. I. BackgroundThis study focuses on developing a decision support tool to provide a graphical representation of the aircraft fuel efficiency environment along the aircraft flight path to aid in trajectory decisions and negotiations with air traffic control. Most aircraft operate off of optimal altitude and speeds during the cruise phase of flight. As shown in Figure 1 below, the typical operating regime for a narrow body jet is faster and off of optimal Mach and altitude in terms of optimal Specific Ground Range (SGR). The SGR is the distance over the ground flown per unit fuel, accounting for wind and temperature. Although speed inefficiency can be accounted for by airline schedule and time related cost constraints, altitude optimization may be possible with the addition of the right decision support tools. Figure 1: Typical Narrow Body Jet Efficiency ContoursDownloaded by PURDUE UNIVERSITY on June 21, 2016 | http://arc.aiaa.org |

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“…Although different algorithms have been developed to lead aircraft to fly at their most efficient trajectories, different studies have pointed out that aircraft did not fly at their optimal altitudes and speeds [13,14]. The set of altitudes and speeds that compose a flight is called the vertical reference trajectory.…”

Section: Introductionmentioning

confidence: 99%

Lateral Reference Trajectory Algorithm Using Ant Colony Optimization

Murrieta-Mendoza

Hamy

Botez

2016

16th AIAA Aviation Technology, Integration, and Operations Conference

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The aeronautical industry requires important quantities of fossil fuel to sustain flights. Fuel burn releases pollution particles to the atmosphere such as carbon dioxide. The aeronautical industry has set itself the goal of diminishing CO 2 emissions for the forthcoming years. A way of reducing fuel consumption is by improving en-route operations. For long haul flights, cruise is the flight stage that requires the most fuel consumption. Taking advantage of tailwinds reduces the flight time, thus reducing the fuel requirements. In this paper, an algorithm based on the Ant Colony Optimization was developed to optimize the lateral navigation reference trajectory of a commercial aircraft. Following a constant flight level, the algorithm was able to identify favorable wind areas, and to lead the aircraft to take advantage of these winds to optimize the flight cost. The aircraft model was a numerical performance model constructed from experimental flight data, where weather information was obtained by using information from Weather Canada. Results showed important fuel savings for different long haul flights. NomenclatureCDA = Continuous Descent Approach CDG = Paris Charles De Gaulle International airport (France) CI = Cost Index LNAV = Lateral Navigation NRT = Tokyo Narita International Airport (Japan) Pherom i = Pheromone level at a given path. PDB = Performance Database P i = Waypoint Selection Probability PTP = International Airport of Point à Pitre (Guadeloupe) TOC = Top of climb TOD = Top of decent VNAV = Vertical Navigation WA = Wind Azimuth WS = Wind Speed YUL = Montreal Pierre Eliot Trudeau International Airport (Canada) γ = Pheromone evaporation rate

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Commercial Airline Speed Optimization Strategies for Reduced Cruise Fuel Consumption

Cited by 40 publications

References 1 publication

New Search Space Reduction Algorithm for Vertical Reference Trajectory Optimization

New Search Space Reduction Algorithm for Vertical Reference Trajectory Optimization

Cruise Altitude and Speed Optimization Implemented in a Pilot Decision Support Tool

Lateral Reference Trajectory Algorithm Using Ant Colony Optimization

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