Electric Aircraft Trajectory Planning Using Real-Time Weather Data
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Solution Overview
Problem
Modern electric aircraft, such as eVTOLs, face challenges in determining optimal flight trajectories due to various factors like destination, weather, and altitude, which existing technologies have not effectively addressed.
Innovation Solution
An electric aircraft equipped with sensors to detect weather measurements and a processor that receives user-inputted destination and altitude data to determine an optimal trajectory, considering health, aerodynamics, and propulsion systems, using machine learning and optimization algorithms for efficient flight planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional flight planning methods are used, then the system is simple to operate, but the flight trajectory cannot be optimized for fuel efficiency and weather conditions
Solution Approach 1:
The flight planning system performs autonomous optimization of flight trajectories by automatically processing weather data, aircraft performance parameters, and mission requirements through onboard processors and machine learning algorithms, eliminating the need for manual flight plan creation while achieving optimal fuel efficiency and weather avoidance
Solution Approach 2:
The system pre-calculates multiple potential flight trajectories before departure and during flight by integrating real-time weather measurements with aircraft performance data, allowing the aircraft to proactively select and adjust to the optimal path rather than reacting to changing conditions
2Reliability
If real-time weather data processing is implemented, then flight safety is improved, but computational requirements and energy consumption increase
Solution Approach 1:
The processor selectively processes only the most critical weather parameters and trajectory variables in real-time, while pre-computing less time-sensitive flight parameters, thereby achieving adequate safety levels without requiring full computational processing of all possible flight variables at maximum intensity
Solution Approach 2:
The flight planning system divides computational tasks into discrete modules: weather data acquisition, trajectory calculation, performance optimization, and safety verification, allowing parallel processing and efficient resource allocation that reduces overall power consumption while maintaining comprehensive safety analysis
3Measurement precision
If multiple weather measurements are collected, then trajectory accuracy is improved, but sensor system complexity increases
Solution Approach 1:
The sensor system uses multi-functional sensors that can detect multiple weather parameters (wind speed, temperature, pressure, humidity) simultaneously, and the processor integrates these diverse measurements with aircraft performance data through unified algorithms, achieving high trajectory accuracy without requiring separate specialized sensors for each parameter
Data Source
AI summary
An electric aircraft with flight trajectory planning. The electric aircraft includes a sensor. The sensor is coupled to the electric aircraft. The sensor is configured to detect a plurality of weather measurements. The electric aircraft includes a processor. The processor is communicatively connected to the sensor. The processor is configured to receive, from the sensor, a weather measurement of the plurality of weather measurements. The processor is configured to receive, from a user, a destination datum and a desired altitude datum. The processor is configured to determine an optimal trajectory of the electric aircraft as a function of the destination datum, weather datum, and altitude datum.