Flight Trajectory Parameterization for Real-Time FMS Optimization
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Solution Overview
Problem
Current Flight Management Systems (FMS) face limitations in processing power, leading to suboptimal flight trajectory planning due to tactical deviations and air traffic constraints, resulting in increased fuel burn and operational costs.
Innovation Solution
A method and system that parameterize optimal flight trajectories using polynomial functions of operational parameters, allowing FMS to quickly determine optimal speed and altitude profiles, even with limited computational power, by precomputing and storing coefficients for various conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Flight Management Systems use traditional trajectory optimization methods, then computational accuracy is improved, but processing time increases and real-time adaptation becomes impossible
Solution Approach 1:
The system pre-computes optimal trajectory parameters and stores them in lookup tables before flight operations. During actual flights, the FMS simply retrieves pre-calculated trajectories based on current flight conditions, eliminating the need for time-consuming real-time optimization calculations while maintaining high accuracy
Solution Approach 2:
The invention transforms the continuous trajectory optimization problem into a discrete parameter selection problem by representing trajectories through key parameters (vertical profile, speed schedule, altitude changes) that can be efficiently stored and retrieved, rather than solving complex differential equations in real-time
2Loss of energy
If Flight Management Systems implement comprehensive trajectory optimization algorithms, then fuel efficiency is improved, but device complexity increases beyond FMS capabilities
Solution Approach 1:
The trajectory optimization problem is divided into separate segments (climb, cruise, descent phases) with distinct optimization parameters for each. This segmentation allows the FMS to handle simpler sub-problems independently using lookup tables, reducing overall computational complexity while achieving fuel efficiency through phase-specific optimization
Solution Approach 2:
Pre-computed lookup tables serve as an intermediary between the complex optimization algorithms and the limited FMS hardware. The heavy computational work is performed offline to create these tables, which then act as a simplified interface that the FMS can query without requiring complex real-time calculations
3Ease of operation
If Cost Index is set for a particular flight, then operational scheduling is simplified, but adaptability to changing flight conditions deteriorates
Solution Approach 1:
The system enables dynamic adjustment of trajectory parameters during flight by allowing the Cost Index to be updated in real-time based on changing conditions (weight, winds, delays). The lookup table structure supports this dynamics by enabling rapid recalculation and retrieval of new optimal trajectories without requiring complex real-time optimization algorithms
Data Source
AI summary
A system and method of generating optimised aircraft flight trajectories on Flight Management Systems with limited computational power that takes into account developing operational conditions, air traffic constraints and aircraft performance in a timely manner on the flight management system that can allow tactical flight plan changes to be incorporated without unduly introducing operational or financial penalties to the operator. An example method involves parameterisation of optimal trajectories as functions of operational parameters thereby allowing computational systems to use such computed functions in the air to determine the optimal trajectory or flight profile required for the specific operating conditions quickly and accurately.