Predictive Radiant Heating Thermostat for Overshoot Control
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Solution Overview
Problem
Conventional heating and cooling systems, particularly radiant heating systems, suffer from overshooting and undershooting due to thermal inertia, leading to inefficient energy use and discomfort, and existing thermostats face challenges in installation and user interface, especially in homes without a 'C' wire for power connection.
Innovation Solution
A thermostat with a processing system that uses predictive controls, including a parameterized model based on historical data to determine optimal control strategies for radiant heating systems, allowing for efficient temperature management without the need for a 'C' wire or household line current, featuring a user-friendly interface and wireless communication capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional heating control systems are used, then the system is simple to implement, but the system suffers from overshooting and undershooting due to thermal inertia, leading to energy inefficiency and discomfort
Solution Approach 1:
The control system performs preliminary actions by predicting future temperature trends based on historical data and thermal models before overshooting or undershooting occurs. The system proactively adjusts heating operations in advance to prevent temperature deviations, rather than reactively responding after the problem occurs.
Solution Approach 2:
The system implements continuous feedback loops that monitor actual temperature measurements against predicted temperature trajectories. This feedback mechanism allows the control system to detect deviations early and adjust heating operations to maintain optimal temperature, preventing energy waste from overshooting and undershooting.
2Ease of manufacture
If electronic thermostats are used without a C wire, then power stealing methods can be employed to avoid additional wiring, but the thermostat must rely on power stealing which limits its functionality and reliability
Solution Approach 1:
The thermostat performs self-service by automatically detecting the presence of a C wire through impedance measurement and other electrical characteristics analysis. The system autonomously determines its power supply configuration and adapts its operation accordingly, eliminating the need for manual installation configuration or user intervention.
Solution Approach 2:
The system changes its operational parameters based on the detected power supply configuration. When a C wire is detected, the thermostat switches to a more reliable power mode with enhanced functionality. When no C wire is present, it adapts to power-stealing mode with adjusted operational characteristics, optimizing performance for each scenario.
3Ease of operation
If radiant heating systems operate with conventional control, then the system is easy to control, but thermal inertia causes the ambient temperature to continue rising above setpoint after heating discontinuation (overshooting) and falling below setpoint after heating resumption (undershooting)
Solution Approach 1:
The control system takes preliminary action by predicting the thermal response of the radiant heating system before making control decisions. Using historical temperature data and thermal models, the system anticipates how long heating effects will persist after shutdown and how long it will take for temperature to drop to setpoint after restart, allowing it to pre-adjust control timing to prevent overshooting and undershooting.
Data Source
AI summary
Embodiments of the invention describe thermostats that use model predictive controls and related methods. A method of controlling a thermostat using a model predictive control may involve determining a parameterized model. The parameterized model may be used to predicted ambient temperature values for an enclosure. A set of radiant heating system control strategies may be selected for evaluation to determine an optimal control strategy from the set of control strategies. To determine the optimal control strategy, a predictive algorithm may be executed, in which each control strategy is applied to the parameterized model to predict an ambient temperature trajectory and each ambient temperature trajectory is processed in view of a predetermined assessment function. Processing the ambient temperature trajectory in this manner may involve minimizing a cost value associated with the ambient temperature trajectory. The radiant heating system may subsequently be controlled according to the selected optimal control strategy.