Aircraft Speed Management Using Aircraft-Specific Fuel Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cost index models for aircraft do not accurately reflect the fuel consumption and performance of specific aircraft, leading to inefficient speed adjustments that either increase fuel consumption or fail to effectively reduce delays.
Innovation Solution
Implementing an aircraft-specific fuel consumption model using machine learning to determine a cost index that optimizes speed adjustments for reducing delays while minimizing fuel consumption, taking into account unique performance metrics of individual aircraft.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If aircraft flies at faster speed to reduce delay, then arrival time is improved, but fuel consumption increases
Solution Approach 1:
The system changes the cost index parameter based on aircraft-specific fuel consumption characteristics. By adjusting this parameter, the flight management system can optimize speed adjustments that reduce delays while minimizing fuel consumption penalties, rather than using generic cost index values that do not account for individual aircraft performance variations.
Solution Approach 2:
The system uses real-time feedback from aircraft-specific fuel consumption models to continuously adjust speed recommendations. The feedback loop incorporates actual aircraft performance data, weather conditions, and flight phase information to dynamically optimize the cost index, enabling the system to balance delay reduction with fuel efficiency based on current operational conditions.
2Device complexity
If generic cost index models are used for speed management, then device complexity is reduced, but measurement precision of fuel consumption deteriorates
Solution Approach 1:
The system segments the fuel consumption modeling by creating aircraft-specific models for each individual aircraft rather than using a single generic model. This segmentation allows each aircraft's unique performance characteristics to be captured, improving measurement precision while maintaining manageable complexity through standardized modeling approaches for each aircraft type.
Solution Approach 2:
The system transitions from static generic cost index models to dynamic aircraft-specific models that adapt to changing flight conditions. The models dynamically adjust based on flight phase, atmospheric conditions, and real-time performance data, improving accuracy without requiring excessively complex structures by leveraging available sensor data and standardized computational approaches.
Data Source
AI summary
A computer implemented method for managing a current speed of an aircraft. A number of processor units identify a delay in an arrival time for reaching a destination location for a current flight of the aircraft. The number of processor units determines a new speed for reducing the delay during the current flight of the aircraft based on a state of the aircraft that optimizes a number of performance metrics for the aircraft using an aircraft specific fuel consumption model for the aircraft.