Mesh Network HVAC Balancing Using Autonomous Damper Nodes
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Solution Overview
Problem
Conventional HVAC systems face challenges in achieving uniform temperature distribution across different rooms due to unequal airflows, varying room geometries, and dynamic changes within buildings, leading to inefficiencies and premature component wear.
Innovation Solution
A mesh network-based HVAC balancing and optimization system that includes active control devices with flow control elements, sensors, and processors to dynamically adjust airflow or heating/cooling based on local and remote sensor data, eliminating the need for a centralized controller and reducing installation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If electronic dampers with centralized control systems are installed to dynamically adjust airflow, then temperature distribution uniformity is improved, but device complexity and installation cost increase significantly
Solution Approach 1:
The system divides the HVAC control into independent autonomous nodes (smart dampers and thermostats) that each make local decisions based on their sensor data, eliminating the need for a complex centralized control system while achieving coordinated temperature distribution across multiple zones
Solution Approach 2:
Each damper and thermostat becomes a self-sufficient intelligent node that autonomously senses local conditions and adjusts airflow without requiring constant communication with or control from a centralized hub, reducing overall system complexity while maintaining dynamic temperature control
2Adaptability or versatility
If standalone processing systems with centralized hubs are used to control electronic dampers, then dynamic airflow adjustment capability is improved, but ease of operation and installation difficulty worsen
Solution Approach 1:
The control system is segmented into independent intelligent nodes (dampers with embedded processors and thermostats) that can operate autonomously, eliminating the requirement for complex centralized hubs and networking infrastructure, thereby simplifying installation while preserving dynamic adjustment capabilities
Solution Approach 2:
The system maintains dynamic airflow adjustment capability through autonomous real-time sensing and actuation at each node, allowing the system to adapt to changing conditions without requiring complex centralized processing or extensive installation infrastructure
3Device complexity
If static dampers are installed to affect air flow rates, then device complexity is reduced, but adaptability to dynamic building conditions deteriorates
Solution Approach 1:
The system transforms static dampers into dynamic intelligent nodes equipped with sensors and processors that can autonomously adjust airflow in real-time based on local temperature and occupancy conditions, maintaining simplicity while achieving adaptability to dynamic building conditions
Solution Approach 2:
Each intelligent node continuously senses local environmental conditions and uses this feedback to autonomously adjust its airflow, enabling the system to adapt to dynamic building conditions without increasing overall complexity through simple local control loops
Data Source
AI summary
Certain aspects of the present disclosure relate to a system including a first active control device, comprising: a flow control element; one or more sensors; a network interface configured to connect to a mesh network; a memory comprising computer-executable instructions; and a processor configured to: execute the computer-executable instructions; receive local sensor data from the one or more sensors; receive remote sensor data from a remote sensing device; control a position of the flow control element based on one or more of the local sensor data or the remote sensor data; store the local sensor data and remote sensor data in the memory; and transmit the local sensor data and the remote sensor data to a second active control device via the mesh network.