Multi-Zone HVAC Stage Control for Persistent Temperature Droop
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Solution Overview
Problem
Existing HVAC control systems face inefficiencies, particularly at high stages, due to 'droop' issues where they fail to fully meet demands, operating for long periods with only slight deviations from set points, especially in multi-zone systems.
Innovation Solution
The proposed stage control algorithm incorporates the integral of system demands over time, weighting cumulative demands to adjust staging demands, allowing for more accurate determination of required capacity stages by considering both positive and negative demands, and consolidating zone demands before integration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the known control algorithm multiplies system demand by a multiplier to select stage, then the control is simple and suitable for low load operations, but the system cannot fully meet demand at high stages and operates for long periods with temperature deviations (droop)
Solution Approach 1:
The control algorithm transitions from a static demand-based stage selection to a dynamic algorithm that continuously integrates demand over time. The staging demand is calculated as Staging Demand = (System Demand × Multiplier) + Integral of System Demand, allowing the system to dynamically adjust stages based on both current and cumulative demand, thereby reliably meeting demand even at high loads.
2Power
If the system operates at high stages with the known control, then the system can handle high demand, but a few degrees difference is never sufficient to move into the next higher stage operation causing droop
Solution Approach 1:
The control algorithm incorporates feedback through integral control, where the cumulative demand (integral of temperature deviations over time) feeds back into the stage selection decision. This ensures that even small persistent temperature deviations accumulate and trigger a stage increase, making the system responsive to sustained demand while maintaining the ability to handle high peak demands.
3Speed
If the control only considers current system demand, then the response is immediate, but the system fails to account for sustained demand over time leading to droop
Solution Approach 1:
The control algorithm performs preliminary action by continuously integrating demand over time before making stage decisions. The integral term accumulates past demand information, allowing the system to anticipate sustained demand patterns and proactively adjust stages before significant temperature deviations occur, thereby reliably meeting both immediate and sustained demand requirements.
Data Source
AI summary
A control for controlling a multi-zone HVAC system, wherein the heating or cooling equipment is operable in multiple stages, takes the demand on the system over time into account when determining an appropriate stage. In particular, a time integral of the system demands is utilized along with a current system demand to determine an appropriate stage. In this manner, a weakness in the prior art of allowing a long-term, small difference between the desired set point and the actual temperature in the various zones is addressed.