Pump Model Self-Calibration for Sensorless Operating Point Control
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Solution Overview
Problem
Existing pump control systems face challenges in accurately controlling pumps without flow sensors, as they rely on uncertain model functions that do not account for manufacturing tolerances, variant differences, and dynamic changes due to wear, requiring precise flow measurements or estimations.
Innovation Solution
A pump control system that automatically updates model parameters using readily available operating values like power consumption or motor current, adjusting model functions based on actual operating values outside predefined ranges to align with true pump characteristics, without needing flow measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If pump control systems use manufacturer-provided model functions to describe pump characteristics, then the control system can operate without flow sensors, but the model accuracy deteriorates due to manufacturing tolerances, variant differences, and dynamic changes over time
Solution Approach 1:
The system automatically adapts model parameters (a, b, c in the polynomial function) based on actual operating data. The control electronics continuously update the model parameters to reflect the true pump characteristics, which change over time due to wear and manufacturing variations. This dynamic parameter adjustment resolves the contradiction by maintaining model accuracy without requiring flow sensors or complex manufacturing processes.
Solution Approach 2:
The pump control system performs self-calibration by using its own operating data (power consumption, motor current, speed) to automatically update its model parameters. The system serves itself by detecting deviations between predicted and actual operating points and adjusting the model accordingly, eliminating the need for external flow sensors or manual calibration procedures.
2Measurement precision
If flow sensors are installed to measure actual flow values for precise pump control, then measurement precision improves, but device complexity and cost increase
Solution Approach 1:
The system extracts the flow measurement function from physical sensors and implements it virtually through mathematical modeling. By using the polynomial model function P(q) = a·q³ + b·q² + c·q and comparing predicted power consumption with actual measurements, the system derives flow information without physical flow sensors, thereby reducing device complexity while maintaining measurement precision.
Solution Approach 2:
The patent replaces mechanical flow sensors with an electronic/software-based solution. The control electronics use electrical measurements (power, current) and mathematical algorithms to infer flow characteristics, substituting mechanical measurement devices with electronic computation to reduce system complexity and cost.
3Device complexity
If the pump model is fixed based on manufacturer data, then device complexity is reduced, but the model becomes unreliable over time due to wear and tear of components
Solution Approach 1:
The patent transforms the static manufacturer-provided model into a dynamic adaptive model. The model parameters are continuously updated based on actual operating conditions and performance data. This dynamic adaptation allows the model to track the pump's changing characteristics over time due to wear, maintaining reliability without complex manual intervention.
Solution Approach 2:
The system implements feedback loops where actual operating measurements (power consumption, motor current) are continuously compared with model predictions. When deviations are detected, the model parameters are adjusted to correct the discrepancies. This feedback mechanism ensures the model remains reliable over time by automatically compensating for wear and operational changes.
Data Source
AI summary
A method controls a pump, with the following steps: running a pump at a set pump speed (ω) based on an operating value model function (Pω(q)) corresponding to the set pump speed (ω); determining an actual operating value (P) at the set pump speed (ω); comparing the actual operating value (P) with a maximum (Pmax) of the operating value model function (Pω(q)) and/or a minimum (Pmin) of the operating value model function (Pω(q)); and automatically updating the operating value model function (Pω(q)) to a higher new operating value model function (Pω,up(q)) if the actual operating value (P) is higher than the maximum (Pmax) of the operating value model function (Pω(q)), and/or automatically updating the operating value model function (Pω(q)) to a lower operating value model function (Pω,down(q)) if the operating value (P) is lower than the minimum (Pmin) of the operating value model function (Pω(q)).