Airflow Model Updating for Real-Time Air-Conditioning Control
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Solution Overview
Problem
Air-conditioning systems face challenges in maintaining energy efficiency due to varying operational conditions and the complexity of airflow models, which are difficult to accurately represent in real-time control applications, especially when installation-specific characteristics and changes in the environment are considered.
Innovation Solution
A method and system that utilize a reduced order model of airflow dynamics, transforming partial differential equations into ordinary differential equations, allowing for real-time updates and control by determining and updating the model's coefficients to minimize tracking errors and adapt to changing conditions, thereby optimizing system performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a physical model of airflow is used to optimize air-conditioning system operation, then the system can account for installation-specific characteristics and improve control accuracy, but the model becomes too complex (infinite dimension) to be used in real-time control applications
Solution Approach 1:
The patent segments the complex airflow model into a simplified representation that captures only the essential dynamics needed for real-time control. By dividing the infinite-dimensional physical model into a finite-dimensional reduced-order model, the system retains sufficient accuracy for control applications while eliminating excessive complexity.
Solution Approach 2:
The patent extracts the critical dynamic characteristics from the full physical airflow model, separating the essential behavior needed for control from the redundant details. This extraction process creates a reduced-order model that maintains control accuracy while removing the computational burden of the complete infinite-dimensional model.
2Use of energy by moving object
If a mathematical model accurately describes the vapor compression system at one point in time, then energy efficiency can be optimized, but the model becomes inaccurate over time as the system changes due to refrigerant leakage or corrosion accumulation
Solution Approach 1:
The patent implements a dynamic model updating mechanism that adapts the system model to changing operational conditions over time. Rather than using a static model that degrades with system aging, the controller continuously updates the model parameters to reflect current system state, maintaining accuracy despite refrigerant leakage or corrosion.
Solution Approach 2:
The patent employs feedback mechanisms where the controller uses real-time system performance data to update and refine the mathematical model. This closed-loop approach ensures the model remains accurate over time by continuously adjusting to actual system behavior, compensating for degradation from refrigerant leakage or corrosion accumulation.
3Productivity
If the controller uses a reduced order model with fewer parameters, then real-time updates and control become feasible, but the model requires iterative coefficient determination to minimize tracking errors
Solution Approach 1:
The patent performs preliminary determination of model coefficients through iterative optimization before real-time control execution. By pre-calculating and storing optimal coefficient values that minimize tracking errors, the system prepares the reduced-order model in advance, enabling fast real-time control without performing complex optimization during operational cycles.
Data Source
AI summary
A method controls an operation of an air-conditioning system generating airflow in a conditioned environment. The method updates a model of airflow dynamics connecting values of flow and temperature of air conditioned during the operation of the air-conditioning system. The model is updated interactively iteratively to reduce an error between values of the airflow determined according to the model and values of the airflow measured during the operation. Next, the method models the airflow using the updated model and controls the operation of the air-conditioning system using the model.