Flight Control Dynamic Pressure Estimation Without Pitot Data
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Solution Overview
Problem
Flight control systems face challenges in accurately determining dynamic pressure when pitot tubes are blocked, leading to inaccurate airspeed calculations and potential aircraft instability, as existing methods rely heavily on pitot tube data and lack robust fault detection mechanisms.
Innovation Solution
A flight control system that calculates an estimated dynamic pressure using a Kalman filter based on lift and drag coefficients, combined with measured accelerations and net thrust, allowing for fault detection and switching to alternative airspeed calculations when pitot tube failures are detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pitot tube data is used for dynamic pressure calculation, then airspeed measurement is simple and direct, but accuracy deteriorates when pitot tubes are blocked
Solution Approach 1:
The patent introduces an intermediary estimation system that uses lift and drag coefficients as mediators to calculate dynamic pressure independently of pitot tubes. When pitot tubes are blocked, this intermediary calculation path provides accurate dynamic pressure values without relying on the faulty pitot tube measurements, thus resolving the contradiction between measurement simplicity and fault reliability.
Solution Approach 2:
The patent changes the parameters used for dynamic pressure calculation from direct pitot tube pressure measurements to aerodynamic coefficients (lift coefficient CL and drag coefficient CD) combined with aircraft state parameters. This parameter transformation creates an alternative calculation pathway that maintains accuracy even when original pressure measurement parameters are compromised by blockages.
2Reliability
If alternative dynamic pressure estimation methods are implemented, then fault detection capability is improved, but device complexity increases
Solution Approach 1:
The patent makes the flight control computer perform multiple functions: it simultaneously calculates aircraft state parameters, determines aerodynamic coefficients, estimates dynamic pressure, and detects faults. By making the existing computer multi-functional rather than adding separate dedicated systems, the patent improves fault detection capability while minimizing the increase in device complexity.
Solution Approach 2:
The patent implements feedback mechanisms where the estimated dynamic pressure and aircraft state parameters are continuously compared with actual measurements. This feedback loop enables automatic fault detection and system self-validation, improving reliability through intelligent monitoring rather than through complex hardware redundancy.
Data Source
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AI summary
A flight control system for an aircraft is disclosed. The flight control system includes one or more processors and a memory coupled to the processors. The memory stores data comprising a database and program code that, when executed by the one or more processors, causes the flight control system to receive as input a plurality of first operating parameters that each represent an operating condition of the aircraft. The flight control system is further caused to determine a drag coefficient and a lift coefficient based on the plurality first of operating parameters. The flight control system is also caused to determine an estimated dynamic pressure based on both the drag coefficient and the lift coefficient.