Method and apparatus for obtaining thermal property data
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Solution Overview
Problem
Current temperature control systems for heating and cooling, such as central heating and air conditioning, lack energy efficiency and fail to provide optimal comfort, as they do not account for the thermal properties of the building or external conditions, leading to inefficient energy use and inadequate temperature control, especially in systems like heat pumps.
Innovation Solution
A method and apparatus for obtaining thermal property data through monitoring temperatures and heat transfer, using statistical inference to determine thermal parameters, which can predict temperature changes and optimize energy use without altering the system's operation or temperature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a thermostat with hysteresis is used to control temperature by targeting a set point, then the system is simple to operate and easy to implement, but energy efficiency is poor and thermal performance insight is lost
Solution Approach 1:
The system performs preliminary action by determining thermal properties (heat capacity, thermal conductance) before optimization control is implemented. This allows the system to predict future temperature changes and plan energy usage in advance, rather than simply reacting to current temperature deviations as a basic thermostat does.
Solution Approach 2:
The system implements feedback by continuously monitoring temperature changes and using this information to update the thermal model. The determined thermal properties are used to predict future temperature behavior, and this predictive information feeds back into the control strategy to optimize energy efficiency while maintaining comfort.
2Loss of energy
If thermal property data is obtained through statistical inference and modeling, then energy efficiency and predictive capability are improved, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically determining its own thermal properties through statistical inference from operational data. The microprocessor analyzes temperature changes and heat transfer patterns to build a thermal model of the specific building, eliminating the need for manual measurements or complex installation procedures.
Solution Approach 2:
The system applies parameter changes by using statistical methods to estimate thermal properties (heat capacity, thermal conductance) from operational data. These determined parameters are then used to predict future temperature behavior and optimize control strategies, transforming raw temperature data into actionable thermal model parameters.
3Measurement precision
If the thermal response of the house is not accurately predicted, then the control system is simple, but the thermal performance and energy requirements cannot be accurately determined
Solution Approach 1:
The system replaces mechanical measurement methods with computational analysis. Instead of using complex physical measurement equipment to directly measure thermal properties, the system uses a microprocessor to analyze temperature data and calculate thermal characteristics through statistical inference and mathematical modeling.
Solution Approach 2:
The system transforms temperature measurement data into thermal performance information by determining key parameters such as heat capacity and thermal conductance. These parameter changes enable the system to predict future temperature behavior and provide insight into thermal performance that goes beyond simple temperature monitoring.
Data Source
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AI summary
In a method of apparatus for obtaining thermal property data on thermal properties of a temperature controlled system which includes temperature control apparatus, said data being suitable for use in predicting the temperature of at least part of the system, the following steps are performed: (a) the monitoring the temperature of at least part of the system over a succession of portions or points of a data acquisition period and recording said temperature for each portion or point in an electronic memory; (b) the determining heat transfer data for the period, said heat transfer data being indicative of the amount of hear energy supplied to, or removed from said part over the acquisition period; and determining the thermal property data from the recorded temperatures and heat transfer data, wherein the thermal property data is determined by a process of statistical inference.