Detecting diagnostic events in a thermal system
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Solution Overview
Problem
Existing thermal systems lack the ability to learn and accurately characterize heat transfer characteristics, leading to inefficient energy use and potential malfunctions due to unknown or unreliable information about zone geometry and thermal properties.
Innovation Solution
An adaptive filter bank is implemented to characterize heat transfer in thermal systems by interacting with thermal devices and weather models, extracting information from passive observations to determine thermal coefficients without requiring commissioning data, and providing diagnostic alerts for anomalous operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If thermal models use commissioning information to characterize heat transfer, then measurement precision improves, but device complexity increases
Solution Approach 1:
The thermal model performs self-characterization by automatically extracting heat transfer coefficients from operational data without requiring external commissioning information. The system uses passive observation of temperature and power consumption data to determine thermal properties, eliminating the need for manual commissioning procedures while maintaining accurate heat transfer characterization.
Solution Approach 2:
The system transitions from using fixed commissioning parameters to dynamically determining thermal coefficients from operational data. By changing the approach from static parameter input to dynamic parameter extraction, the system achieves accurate heat transfer characterization without the complexity of commissioning information collection and input.
2Ease of operation
If thermal models extract information from passive observations, then ease of operation improves, but reliability deteriorates due to unknown or unreliable zone geometry and thermal properties
Solution Approach 1:
The system uses feedback from operational data to continuously refine and verify thermal coefficient estimates. By monitoring the consistency between predicted and actual temperature behavior, the system can detect and correct errors in heat transfer characterization, maintaining reliability while operating without commissioning information.
Solution Approach 2:
The thermal model transitions from static commissioning-based parameters to dynamic coefficient determination that adapts to actual system behavior. The system continuously updates thermal properties based on observed operational patterns, making the characterization more reliable over time while maintaining ease of operation.
3Device complexity
If thermal systems operate without accurate heat transfer characterization, then device complexity decreases, but loss of energy increases due to inefficient temperature control
Solution Approach 1:
The system automatically determines optimal temperature control strategies by extracting thermal coefficients from operational data, enabling energy-efficient operation without manual commissioning. The self-characterization process provides the necessary information for optimal control while maintaining simplicity in deployment.
Data Source
AI summary
Embodiments of the disclosure provide a thermal model based on an adaptive filter bank for characterizing heat transfer of a volume of a thermal system. In one embodiment, the adaptive filter bank is used for diagnostics that provides information related to the condition of a thermal system. The diagnostics are based on an analysis of heat transfer characteristics of a dynamic representation of the thermal system. In accordance with the embodiments, thermal coefficients are generated based on an adaptive filter bank. One or more filters are applied to the thermal coefficients based on a sampling rate and one or more estimate thermal coefficient thresholds are generated based on the sampling rate. It is determined whether at least one of the thermal coefficients that is filtered satisfies at least one of the estimated thermal coefficient thresholds. Thereupon, alert information indicative of a diagnostic event is provided based on the determination.