Aircraft Takeoff Weight Estimation via Trajectory Data

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Solution Overview

Problem

Accurate estimation of aircraft takeoff weight is crucial for efficient aircraft management, but direct measurement is impractical, and existing methods rely on data available only to specific aircraft or airlines.

Innovation Solution

A method that generates input parameters from trajectory data, including subsets for the takeoff and climb phases, and processes these using a trained model to estimate the takeoff weight of an aircraft, leveraging publicly available information.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If direct measurement of takeoff weight is performed, then measurement precision is improved, but ease of operation deteriorates due to impracticality

Engineering Contradiction:

Improvetakeoff weight measurement precisionVSAvoidease of takeoff weight measurement

Core Design Contradiction:

Measurement precisionVSEase of operation

Solution Approach 1:

The patent uses trajectory data as an intermediary to indirectly determine takeoff weight. Instead of directly measuring weight, the system processes flight trajectory information (position, altitude, speed over time) through machine learning models to estimate takeoff weight, making the measurement process practical and operable while maintaining accuracy

Inventive Principle:

Principle #24Intermediary (Mediator)

Solution Approach 2:

The patent replaces physical/mechanical weight measurement systems with an information processing system. Rather than using physical scales or mechanical weighing devices at the airport, the system substitutes a computational approach using trajectory data and machine learning algorithms to determine takeoff weight

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Ease of operation

If existing estimation methods are used, then ease of operation is improved, but measurement precision deteriorates due to reliance on restricted data

Engineering Contradiction:

Improveease of takeoff weight estimationVSAvoidtakeoff weight estimation precision

Core Design Contradiction:

Ease of operationVSMeasurement precision

Solution Approach 1:

The patent creates a universal estimation method that works for any aircraft without requiring airline-specific or aircraft-specific proprietary data. The machine learning model is trained on general trajectory data and can estimate takeoff weight for different aircraft types using publicly available flight information, making the system universally applicable while maintaining precision

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent changes the input parameters from restricted operational data to publicly available trajectory data. By using position, altitude, and speed information from flight trajectories (which are publicly broadcast), the system transforms the estimation problem into one that can be solved with accessible data while maintaining or improving accuracy through advanced processing

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS20250180395A1Systems and methods for aircraft takeoff weight estimation

Publication Date: 2025.06.05 THE BOEING CO

AI summary

Systems and methods for aircraft takeoff weight estimation include receiving input data corresponding to trajectory data of a flight of an aircraft; generating a set of input parameters based on the trajectory data, where the set of input parameters include a first subset of parameters corresponding to a takeoff phase of the flight and a second subset of parameters corresponding to a climb phase of the flight; and processing the set of input parameters using a trained model to generate an estimate of a takeoff weight of the aircraft.