Prognostic Flow Sensor BIT for Motor-Driven Compressor
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Solution Overview
Problem
Current flow sensor BITs for motor-driven compressors in environmental control systems, such as those used in aircraft, are unable to accurately detect failure modes that cause compressor surges, leading to inefficiencies and instability due to unreliable readings, and existing redundant configurations increase costs and complexity.
Innovation Solution
A computer-implemented method and system for a prognostic flow sensor BIT that estimates airflow based on motor power and temperature differentials, comparing measured airflow values to estimated values to identify malfunctions and transmit event notifications, thereby reducing CAC surges and improving system efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a redundant flow sensor configuration is used to detect sensor drift, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent introduces a virtual flow meter as an intermediary computational model that estimates actual airflow based on motor parameters (power, speed, temperature differentials). This virtual sensor acts as a mediator between the physical flow sensor and the control system, providing a reference value for detecting sensor drift without requiring redundant physical sensors.
Solution Approach 2:
The patent replaces the mechanical/redundant physical sensor configuration with a computational/virtual sensing system. Instead of using multiple physical flow sensors to detect drift, the system uses a mathematical model (virtual flow meter) that processes motor parameters to estimate airflow, thereby substituting physical redundancy with computational analysis.
2Productivity
If flow sensor readings are used to control motor power, then productivity is improved, but reliability deteriorates when sensors malfunction
Solution Approach 1:
The patent implements a feedback mechanism where the virtual flow meter continuously monitors estimated airflow and compares it with actual sensor readings. When discrepancies indicate sensor malfunction, the system generates alerts and can switch to using virtual sensor data for control decisions, ensuring continuous reliable operation.
Solution Approach 2:
The patent prepares for potential sensor failures by pre-establishing the virtual flow meter computational model and detection algorithms. This beforehand cushioning ensures that when sensor malfunctions occur, the system already has an alternative method for determining airflow, preventing disruptions to compressor operation.
3Measurement precision
If flow sensor accuracy is maintained within +/- 6%, then measurement precision is improved, but device complexity increases due to additional detection mechanisms
Solution Approach 1:
The patent makes the virtual flow meter serve multiple functions: it acts as a reference for detecting sensor drift, provides backup airflow data when sensors fail, and enables continuous monitoring of sensor health. This multi-functionality eliminates the need for separate detection mechanisms while maintaining precision requirements.
Data Source
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AI summary
According to one embodiment, a computer-implemented method for prognostic for flow sensor is provided. The method includes receiving a first input, the first input related to an input power of a motor for driving a compressor, and receiving a second input, the second input related to a temperature differential of the compressor. The method also includes calculating an estimated airflow based on the first input and the second input, and exporting data associated with the first input, the second input, and the estimated airflow.