HVAC controller with predictive set-point control
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Solution Overview
Problem
HVAC systems face challenges in effectively controlling humidity levels to prevent condensation on window panels, especially when internal and external temperature conditions vary, leading to inefficient climate regulation.
Innovation Solution
A controller with predictive capabilities that adjusts humidity set points based on calculated humidity limit values, using internal and external temperature values to determine the lowest humidity threshold where condensation occurs on window panels, thereby controlling HVAC equipment to maintain optimal humidity levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional HVAC systems use fixed humidity control, then the control system is simple to operate, but condensation forms on window panels when temperature conditions vary
Solution Approach 1:
The system performs preliminary calculations of the dew point temperature and humidity limit value based on internal and external temperature conditions before condensation occurs. By proactively determining the humidity limit value using the formula involving dew point temperature and window panel temperature, the system prevents condensation formation on window panels before it happens, rather than reacting after condensation has formed.
Solution Approach 2:
The humidity control system transitions from a fixed set-point approach to a dynamic adaptive approach. The humidity limit value is continuously adjusted based on real-time internal and external temperature measurements and predictive temperature values. This dynamic adjustment ensures the humidity control adapts to changing thermal conditions, preventing condensation while maintaining system simplicity through automated calculations.
2Reliability
If HVAC systems dynamically adjust humidity set points based on temperature predictions, then condensation prevention is improved, but energy consumption increases
Solution Approach 1:
The system uses predictive temperature values to anticipate future thermal conditions and pre-adjusts the humidity limit value accordingly. By calculating the humidity limit based on predicted internal and external temperatures rather than current conditions alone, the system proactively prevents condensation during temperature transitions, avoiding the need for more aggressive reactive humidity control that would consume additional energy.
Solution Approach 2:
The system dynamically changes the humidity control parameter (humidity limit value) based on temperature conditions. By adjusting the humidity set-point according to the calculated humidity limit value derived from temperature parameters, the system optimizes energy consumption by maintaining humidity only at levels necessary to prevent condensation, rather than using fixed high humidity settings that would waste energy.
3Measurement precision
If the system uses multiple temperature values including non-current temperatures, then predictive accuracy improves, but calculation complexity increases
Solution Approach 1:
The system performs preliminary determination of predictive temperature values using multiple data points including non-current temperatures before humidity control decisions are made. By pre-calculating these predictive values and storing them for use in humidity limit calculations, the system achieves accurate temperature prediction without adding complexity to the real-time humidity control decision-making process.
Solution Approach 2:
The controller automatically performs the complex calculations of predictive temperature values and humidity limit values using its own processing capabilities. The system serves itself by internally computing the humidity limit value using the formula based on internal and external temperatures, eliminating the need for external complex calculation systems or additional hardware, thus achieving measurement precision without proportional increase in overall system complexity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution enables precise humidity control, preventing condensation and enhancing climate regulation efficiency by dynamically adjusting humidity levels according to predictive temperature and humidity forecasts.
Implementation Method 1
the humidity limit value being the lowest humidity value where condensation would form on the window panel
Data Source
AI summary
A controller is provided for HVAC equipment. The controller receives a set of internal temperature values, and a set of external temperature values, the set of external temperature values representing at least one non-current temperature. The controller determines a predictive internal temperature value from the set of internal temperature values and a predictive external temperature value from the set of external temperature values. The controller receives an internal humidity value representing humidity within the premise, the controller further controls the HVAC equipment to modify the humidity within the premise when the received internal humidity value is different from a humidity set point; and the humidity set point is regulated by a humidity limit value, the humidity limit value being where condensation forms, the humidity limit value being calculated using the predictive internal temperature value and the predictive external temperature value.