Thermostat with predictive variable air volume (VAV) performance features
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Solution Overview
Problem
HVAC systems face challenges in identifying and addressing performance deviations in variable air volume (VAV) units and air handler units due to physical changes or failures within zones, leading to inefficient temperature control and potential equipment malfunctions.
Innovation Solution
A thermostat with a processing circuit that compares time-series data from similar VAV units and zones to detect performance deviations, generates recommendations for improving equipment operation, and controls environmental conditions by adjusting parameters or suggesting maintenance, using exponentially weighted moving averages (EWMA) and rule-based analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If VAV units and zones are assumed to perform similarly, then system control is simplified, but performance deviations due to failures or physical changes cannot be detected
Solution Approach 1:
The system continuously monitors performance parameters from multiple VAV units and compares them against each other and against expected performance patterns. This feedback mechanism enables detection of deviations caused by equipment failures or physical changes while maintaining automated control.
Solution Approach 2:
A cloud-based platform acts as an intermediary between the HVAC equipment and the control system. This platform receives data from multiple VAV units, performs comparative analysis, and generates control recommendations, thereby detecting performance deviations without adding complexity to individual zone controllers.
2Reliability
If performance analysis is performed on all VAV units individually, then performance deviations can be detected, but system complexity and computational requirements increase
Solution Approach 1:
The system combines data from multiple VAV units into a unified analysis framework. By merging performance data across zones and comparing relative performance, the system detects deviations efficiently without requiring separate complex analysis for each unit, leveraging the redundancy of similar equipment.
Solution Approach 2:
A single cloud-based platform performs multiple functions: data collection from various VAV units, comparative performance analysis, failure detection, and control recommendation generation. This universal platform handles all analysis tasks centrally, reducing individual device complexity while maintaining comprehensive monitoring.
3Loss of time
If real-time monitoring and comparison of multiple VAV units is implemented, then performance issues are identified quickly, but data transmission and processing requirements increase
Solution Approach 1:
The system extracts only the essential performance parameters needed for comparison (such as temperature control performance, energy consumption patterns) from the full set of available data. By transmitting and analyzing only these critical parameters, the system achieves rapid performance issue identification while minimizing data transmission requirements.
Data Source
AI summary
A thermostat for includes a processing circuit configured to operate the building equipment to control an environmental condition within a building including a first zone and second zones and receive a first time-series data set for a parameter of a first piece of the building equipment associated with the first zone. The processing circuit is configured to receive second time-series data sets for the parameter of second pieces of building equipment associated with the second zones. The processing circuit is configured to perform a comparison including comparing the first time-series data set with the second time-series data sets and generate recommendations for improving the performance of the first piece of building equipment based on the comparison of the first time-series data set with the second time-series data sets.