Electric Aircraft Flight Planning for Battery Reserve State of Charge
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Solution Overview
Problem
Existing electric aircraft technologies face challenges in calculating and ensuring a performance reserve requirement for flight, as the nonlinear nature of electric battery energy supply and varying battery conditions make it difficult to determine the necessary reserve state of charge for completing flights, unlike petroleum-based fuel systems.
Innovation Solution
A computing system that computes a reserve state of charge for electric aircraft based on battery characteristics, flight plans, and real-time data, using look-up tables and machine-learned algorithms to account for factors like battery age, usage history, and environmental conditions, and adjusts flight parameters such as payload to ensure compliance with performance reserve requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional petroleum-based fuel systems are used for flight, then performance reserve requirements can be easily calculated and ensured, but electric aircraft cannot reliably determine the necessary reserve state of charge due to nonlinear battery energy supply characteristics
Solution Approach 1:
The system performs preliminary computation of the reserve state of charge before flight operations by accessing battery conditions and applying lookup tables or machine-learned algorithms. This advance calculation ensures that the performance reserve requirement is determined prior to flight, allowing for proper flight planning and battery charging parameter computation without relying on complex real-time calculations during flight.
Solution Approach 2:
The patent introduces an intermediary computing system that acts as a mediator between the battery system and flight planning. This intermediary system processes battery conditions through lookup tables or machine-learned algorithms to translate complex nonlinear battery characteristics into reliable reserve state of charge values, simplifying the determination process while maintaining accuracy.
2Reliability
If battery charging parameters are adjusted to ensure performance reserve requirements, then flight reliability improves, but preflight activity time and operational efficiency may be reduced
Solution Approach 1:
The system computes battery charging parameters in advance during flight planning, determining the exact charging duration and power levels needed to achieve the required reserve state of charge. This preliminary computation allows for optimized charging schedules that minimize preflight charging time while ensuring the performance reserve requirement is met, rather than using fixed or conservative charging protocols.
Solution Approach 2:
The system dynamically adjusts battery charging parameters based on actual battery conditions, flight plans, and environmental factors. By making the charging parameters dynamic rather than static, the system can optimize charging duration and power levels for each specific situation, reducing unnecessary charging time while ensuring the reserve state of charge requirement is achieved.
Data Source
AI summary
Example aspects of the present disclosure relate to battery-based flight planning for electric vehicles. The example method includes accessing a performance reserve requirement associated with aerial operations within an airspace and battery conditions for one or more batteries onboard an electric aircraft. The method includes computing a reserve state of charge for the electric aircraft to complete a future flight within the airspace based on the performance reserve requirements and the battery conditions. The method includes computing one or more battery charging parameters for the electric aircraft to complete the future flight based on the reserve state of charge. The method includes confirming an electric aircraft's ability to perform the future flight, adjusting a preflight activity, or adjusting the future flight based on the battery charging parameters.