Deterministic Genetic Algorithm for RTA-Compliant OPD Trajectories
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Solution Overview
Problem
Aircraft descent profiles using idle thrust are unpredictable and inefficient, leading to increased fuel consumption and carbon emissions, while constant flight path angles provide predictability but require near-idle thrust and speed brakes, posing challenges in integrating Optimal Profile Descent (OPD) into air traffic flow without reducing capacity.
Innovation Solution
A method and apparatus using a Deterministic Genetic Algorithm on an on-aircraft computer to construct a four-dimensional trajectory that complies with path constraints, adjusting altitude, speed, flight path angle, and fuel consumption to produce a feasible OPD flight path, incorporating Required Time of Arrival (RTA) constraints for efficient air traffic management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If idle thrust is used during descent to achieve Optimal Profile Descent, then fuel consumption is reduced, but the descent profile becomes unpredictable and varies between flights
Solution Approach 1:
The system pre-calculates and stores optimal descent profiles in a database before flight, accounting for various aircraft configurations and conditions. During actual descent, the pre-computed profile is selected and executed, ensuring both fuel efficiency and predictability without real-time computation delays
Solution Approach 2:
The system creates a digital replica of the descent profile from pre-computed data and flight parameters, generating a predictable path that can be precisely followed during execution while maintaining the fuel efficiency characteristics of idle thrust descent
2Reliability
If constant flight path angles are used during descent, then the vertical descent profile is predictable, but near-idle thrust and speed brake are required
Solution Approach 1:
The system dynamically adjusts flight path angles during descent based on real-time aircraft state and constraints, rather than using fixed constant angles. This allows the profile to remain predictable through computational control while optimizing thrust usage and avoiding excessive speed brake deployment
3Loss of energy
If Optimal Profile Descent is implemented without RTA constraints, then fuel efficiency is improved, but air traffic capacity around the airport is reduced
Solution Approach 1:
The system pre-calculates descent profiles that incorporate Required Time of Arrival constraints at metering waypoints, ensuring that fuel-efficient OPD can be executed while maintaining scheduled arrival times and preserving air traffic flow capacity
Solution Approach 2:
The system uses RTA constraints as feedback to adjust and optimize the descent profile, allowing the aircraft to maintain fuel efficiency while adhering to air traffic management requirements for timely arrivals and capacity maintenance
Data Source
AI summary
A on-aircraft computer device predicts aircraft states (e.g., altitude, speed, flight path angle, and fuel consumption) at any given time, while utilizing a Deterministic Genetic Algorithm to search 4-D flight path candidates that can comply with all path constraints to produce a feasible 4-D path candidate as a final OPD flight path to arrive at a metering waypoint in a specified time window.