Stochastic Flight Planning Using Ensemble Weather Forecasts
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Solution Overview
Problem
Existing flight planning systems are susceptible to estimation errors, particularly due to inaccurate weather predictions, which can adversely affect flight efficiency, especially for long-haul flights. These systems typically rely on a single weather forecast, failing to account for weather uncertainties between locations.
Innovation Solution
A stochastic flight planning system that utilizes ensemble data from multiple sources to determine a plurality of flight plans. This system includes control units configured to analyze ensemble weather forecast data, fuel consumption information, and air traffic data to identify optimal flight routes, thereby minimizing fuel consumption and accounting for weather uncertainties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a single weather forecast is used to determine flight plan, then the flight planning process is simple and fast, but the accuracy and reliability of fuel consumption estimation deteriorates due to weather uncertainties
Solution Approach 1:
The patent segments the single weather forecast into multiple ensemble weather forecasts from different sources. Instead of relying on one forecast, the system divides the weather prediction into multiple independent forecasts, each contributing to a more comprehensive understanding of weather uncertainties. This segmentation allows the system to evaluate multiple possible weather scenarios and select the optimal flight plan accordingly.
Solution Approach 2:
The patent adds a new dimension to flight planning by incorporating stochastic methods and ensemble data. Rather than a single deterministic flight plan, the system generates multiple flight plans across a probabilistic landscape. This dimensional expansion allows evaluation of flight plans under various weather scenarios, transforming the problem from a single-point optimization to a multi-dimensional probabilistic optimization.
2Reliability
If multiple ensemble weather forecasts are analyzed to account for weather uncertainties, then the reliability of flight plan estimation is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent performs preliminary actions by generating multiple ensemble weather forecasts and evaluating multiple flight plans before the actual flight departure. By conducting this comprehensive analysis in advance, the system establishes a robust probability distribution of fuel consumption outcomes. This preliminary work enables rapid selection of the optimal flight plan when the time comes, avoiding last-minute computational delays.
Solution Approach 2:
The patent replaces traditional deterministic mechanical flight planning with stochastic methods. Instead of following a fixed, deterministic procedure that processes one weather forecast sequentially, the system uses probabilistic models and statistical methods to evaluate multiple scenarios simultaneously. This substitution enables more efficient processing by leveraging mathematical frameworks designed for handling uncertainty and multiple variables.
3Adaptability or versatility
If stochastic methods are used to determine multiple flight plans from ensemble data, then the account for weather uncertainties is improved, but the system complexity and data processing requirements worsen
Solution Approach 1:
The patent implements a universal flight planning system that can handle multiple types of weather forecasts from different sources using the same stochastic framework. The control unit is designed to process various data formats and ensemble configurations uniformly, making the system multi-functional and adaptable to different weather data sources without requiring separate processing mechanisms for each source.
Solution Approach 2:
The patent utilizes parameter changes in the stochastic model to adapt to different weather scenarios and data sources. By adjusting parameters such as probability distributions, correlation coefficients, and forecast weights, the system can accommodate varying levels of uncertainty and different ensemble configurations without changing the fundamental system architecture. This parameter-based adaptability reduces structural complexity while maintaining versatility.
Data Source
AI summary
A flight planning system and method include one or more control units configured to determine, from ensemble data, a plurality of flight plans for an aircraft from a departure location to an arrival location. The ensemble data includes an aggregation of data from multiple data sources. In at least one example, the one or more control units are further configured to determine a preferred flight plan from the plurality of flight plans.