Flight Control Dynamic Pressure Estimation Under Pitot Tube Blockage
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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 speed and altitude calculations, and existing fault detection methods generate spurious alarms.
Innovation Solution
A flight control system that determines an estimated dynamic pressure based on lift and drag coefficients using an extended Kalman filter, allowing for the detection of common mode faults and switching to an extended normal mode of operation to prevent unnecessary system mode changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pitot tubes are used to measure dynamic pressure, then speed and altitude calculations can be performed, but the measurements become inaccurate when pitot tubes are blocked with ice
Solution Approach 1:
The patent introduces an intermediary computational model (extended Kalman filter) that processes multiple sensor inputs (pitot pressure, static pressure, angle of attack, airspeed) to generate an estimated dynamic pressure. This intermediary system provides a backup measurement pathway that remains reliable even when direct pitot tube measurements fail due to blocking.
Solution Approach 2:
The system implements feedback by continuously comparing measured dynamic pressure from pitot tubes with estimated dynamic pressure from the extended Kalman filter. When the difference exceeds a threshold, the system switches to using the estimated value, creating a self-correcting measurement system that maintains accuracy under varying conditions.
2Reliability
If fault detection methods compare measured and estimated dynamic pressure, then pitot tube faults can be detected, but spurious alarms are generated causing unnecessary system mode changes
Solution Approach 1:
The system performs preliminary validation by checking whether the difference between measured and estimated dynamic pressure exceeds a predetermined threshold before triggering a fault alarm. This preliminary action filters out minor discrepancies that would otherwise generate spurious alarms, ensuring that only significant faults trigger system mode changes.
3Productivity
If the system switches to extended normal mode upon fault detection, then continuous operation is maintained, but unnecessary mode changes occur due to spurious alarms
Solution Approach 1:
The system applies preliminary threshold-based filtering to distinguish between normal measurement variations and actual faults, preventing unnecessary mode transitions. By establishing clear decision criteria before mode changes occur, the system maintains operational continuity while avoiding unnecessary complexity in mode management.
Data Source
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 of first 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.