Aircraft Emissions Monitoring via Regional Segmentation
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Solution Overview
Problem
Existing methods for calculating aircraft greenhouse gas emissions are approximate and lack specificity at regional and local levels, failing to provide accurate data for minimizing emissions.
Innovation Solution
A system and method that uses navigation and location data, fuel consumption data, and mathematical models to determine greenhouse gas emissions, correlating them with specific regions of travel, and employs machine learning to predict future emissions based on these correlations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If approximate methods using estimated distance are used to calculate emissions, then calculation simplicity is improved, but measurement precision deteriorates
Solution Approach 1:
The patent segments the flight path into multiple regions (e.g., departure region, arrival region, en-route regions) and calculates emissions for each segment separately using actual navigation data. This segmentation allows the system to maintain calculation simplicity while improving precision by applying region-specific emission factors and actual flight paths rather than single aggregate estimates.
2Measurement precision
If detailed regional and local level data is collected, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent employs a multi-functional system that processes multiple types of data (navigation data, flight parameter data, weather data) through a unified emissions calculation framework. The system can handle different aircraft types, flight phases, and regional variations using a single versatile platform, thereby achieving detailed regional precision without proportionally increasing system complexity.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives raw navigation and flight data, applies mathematical models and emission factors, and produces refined emissions estimates. This intermediary layer simplifies the overall system architecture by centralizing the complex calculations and data transformations in a dedicated module rather than distributing complexity across multiple components.
3Measurement precision
If actual navigation data is used instead of estimated distance, then measurement precision is improved, but loss of time in data processing increases
Solution Approach 1:
The patent applies preliminary actions by pre-calculating and storing emission factors, conversion factors, and regional coefficients before actual emissions calculations are performed. During flight monitoring, the system retrieves these pre-computed values and applies them to actual navigation data, significantly reducing real-time processing time while maintaining high precision based on actual rather than estimated flight paths.
Data Source
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AI summary
The present disclosure is directed to a method and system for monitoring and predicting greenhouse gas emissions for a flight of an aircraft. The system receives navigation and location data of a flight of an aircraft through one or more regions of travel such as an airspace. The system further obtains fuel consumption data of the flight of the aircraft through the one or more regions of travel. Using mathematical models, the system then determines the greenhouse gas emissions of the aircraft through the one or more regions of travel. The system then compares the greenhouse gas emissions of the aircraft with the navigation and location data to determine one or more correlations between the greenhouse gas emissions data and the one or more regions of travel. The system then outputs the correlations to various other systems (e.g., a display or machine learning system) for further analysis and processing.