HVAC On-Off Control with Predictive Time Delay Compensation
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Solution Overview
Problem
HVAC systems experience excessive temperature swings due to thermal inertia, leading to overshoot and undershoot beyond the deadband, which is not effectively addressed by existing control algorithms.
Innovation Solution
A controller that predicts and adjusts for time delays in HVAC systems by using an adjustable time delay parameter, implemented through a processing circuit that filters feedback signals using exponential expansion transfer functions, allowing for improved on-off feedback control and reduced thermal inertia impacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional on-off control algorithms are used, then the HVAC system operates with simple control logic, but temperature swings and overshoot beyond the deadband occur due to thermal inertia
Solution Approach 1:
The controller predicts future temperature values based on historical data and thermal models before the actual temperature deviation occurs. This preliminary prediction allows the system to prepare control actions in advance, compensating for thermal inertia and preventing overshoot beyond the deadband while maintaining simple on-off control logic.
Solution Approach 2:
The system implements a predictive feedback mechanism that uses historical temperature data and thermal models to anticipate future temperature trends. This feedback loop enables the controller to adjust control decisions based on predicted rather than just current temperature states, reducing temperature swings while preserving control logic simplicity.
2Reliability
If minimum on/off times are implemented, then equipment cycling is reduced, but temperature control precision deteriorates due to delayed response
Solution Approach 1:
The predictive controller calculates future temperature states in advance, allowing the system to account for minimum on/off times in its predictions. This enables precise temperature control despite the delayed equipment response, as the control decisions are based on predicted temperatures that already factor in the equipment's response time.
Solution Approach 2:
The system uses its own historical temperature data and thermal models to predict future behavior, making the minimum on/off times work in its favor. The predictor leverages the system's inherent thermal characteristics to improve control precision rather than treating it as a limitation.
3Use of energy by moving object
If deadband control is used, then energy consumption is reduced, but temperature swings increase due to excessive on-off cycling
Solution Approach 1:
The predictive controller anticipates temperature changes before they occur, allowing the system to maintain the deadband strategy for energy efficiency while preventing excessive cycling. By predicting future temperatures, the controller can make more informed on-off decisions that reduce temperature swings without increasing energy consumption.
Solution Approach 2:
The system implements predictive feedback that combines deadband control with future temperature predictions. This enhanced feedback mechanism allows the controller to maintain energy-efficient deadband operation while using predicted temperature trends to reduce excessive cycling and improve temperature stability.
Data Source
AI summary
A controller for HVAC equipment of a plant includes a processing circuit configured to predict an impact of a time delay of the plant on a performance variable received as feedback from the plant. The processing circuit is configured to artificially increase or decrease a value of the performance variable using an adjustable time delay parameter to at least partially negate the impact of the time delay on the performance variable. The processing circuit is configured to use the artificially increased or decreased value of the performance variable in on-off feedback control to operate the HVAC equipment.