Model-Based VAV Control for Multi-Unit HVAC Optimization
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Solution Overview
Problem
Existing HVAC systems face inefficiencies due to poor design, wear, and complex interactions between air-handling units, which rule-based control methods struggle to optimize, leading to suboptimal operation and lack of error identification.
Innovation Solution
A model-based control system utilizing a remote server with heuristic modeling, incorporating sensors for temperature, humidity, fan speed, pressure, and power, to optimize air distribution by determining operational parameters and predicting future behavior, thereby improving operational performance and identifying potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If rule-based control is used for air-handling units, then the control logic is simple and easy to implement, but the system cannot optimize complex interactions between multiple air-handling units and cannot identify improper operation
Solution Approach 1:
A cloud-based server acts as an intermediary between air-handling units, receiving operational data and returning optimized control parameters. This mediator handles the complexity of multi-unit interactions centrally while keeping individual unit controllers simple, resolving the contradiction between ease of operation and adaptability to complex scenarios.
Solution Approach 2:
The patent replaces traditional mechanical rule-based control logic with data-driven analytics and machine learning models running in the cloud. This substitution enables the system to handle complex interactions and identify improper operations through pattern recognition in operational data, while maintaining simple local controllers.
2Reliability
If more sensors and measurements are gathered for air-handling units, then better analytics and predictive capabilities can be achieved, but the system complexity and data processing requirements increase
Solution Approach 1:
The patent extracts complex data processing and analytics functions from local controllers and relocates them to a cloud-based server. This extraction allows comprehensive sensor data to be collected and processed centrally with high computational power, enabling reliable predictive maintenance while keeping individual air-handling units relatively simple.
Solution Approach 2:
The cloud-based server provides universal data processing capabilities that serve multiple air-handling units simultaneously. It performs analytics, predictive maintenance, and optimization for the entire fleet of units, making the complex data processing infrastructure universally applicable across the HVAC system rather than requiring dedicated complex systems at each unit.
Data Source
AI summary
Using information available from the controller or controllers of air-handling units, a remote server uses a heuristic model to determine settings for the air-handling units. Rather than just using rules for each air-handling unit, a model-based solution determines the settings. The model is used to optimize operation of the air distribution. In additional or alternative embodiments, measurements are gathered and used to derive analytics. The measurements may include data not otherwise used for rule-based control of the air handling unit. The analytics are used to predict needs, as inputs to the modeling, identify problems, and/or identify opportunities.