Electric Aircraft Power Source Preconditioning From Flight Plans
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Solution Overview
Problem
Electric aircraft require efficient power source preconditioning to optimize charging times and operational efficiency, but existing methods lack automated and proactive solutions for adjusting power source conditions based on flight plans and operating conditions.
Innovation Solution
A computing device is used to receive flight plans, determine predicted power usage models, and initiate power source modifications by adjusting operating conditions to optimal performance levels, utilizing sensors and machine-learning models to identify divergent elements and automate preconditioning operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated preconditioning systems are implemented, then charging time is reduced and operational efficiency is improved, but device complexity increases
Solution Approach 1:
The system performs preconditioning actions in advance by analyzing the flight plan before departure and adjusting power source parameters proactively. The computing device determines predicted power usage based on the flight plan and initiates power source modifications before the aircraft needs to charge, thereby reducing charging time without requiring complex real-time control systems during charging operations.
Solution Approach 2:
The power source management system autonomously monitors its own operating conditions and automatically initiates preconditioning operations without external intervention. The computing device continuously monitors power source parameters, compares them against optimal conditions, and self-adjusts parameters such as temperature and charge state based on predicted flight requirements, reducing the need for external monitoring and control infrastructure.
2Reliability
If real-time monitoring and adjustment of power source conditions is performed, then optimal performance is achieved, but ease of operation decreases due to increased automation requirements
Solution Approach 1:
The computing device continuously monitors power source operating conditions and compares them against optimal performance parameters. Based on this feedback loop, the system automatically adjusts power source parameters during flight operations to maintain optimal conditions. This automated feedback mechanism ensures reliable power source performance while eliminating the need for manual monitoring and adjustment by operators.
Solution Approach 2:
The system replaces manual mechanical monitoring and adjustment operations with automated electronic control. The computing device uses software algorithms to analyze flight plans, predict power usage, and automatically control power source parameters, substituting complex manual operational procedures with automated computational systems that improve reliability without requiring operator expertise in power source management.
3Productivity
If power source parameters are adjusted based on flight plans, then charging efficiency is improved, but loss of time occurs during parameter analysis and determination
Solution Approach 1:
The computing device analyzes the flight plan and determines predicted power usage parameters before the aircraft departs or before charging operations begin. By performing this analysis in advance rather than in real-time during charging, the system minimizes the time lost to parameter analysis while ensuring that optimal charging parameters are already determined and ready for implementation, thereby maintaining high charging efficiency.
Data Source
AI summary
An apparatus for preconditioning a power source of an electric aircraft is presented. The apparatus includes a power source of an electric aircraft, a computing device, and a user device. The computing device is configured to receive a flight plan, determine a predicted power usage model as a function of the flight plan, and initiate a power source modification on the electric aircraft as a function of the predicted power usage model. The user device is configured to display a flight performance infographic as a function of the predicted power usage model.