Systems and method of identifying heat/cool ingress with a climate control system
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Solution Overview
Problem
Climate control systems in buildings often face inefficiencies due to uncontrolled heating or cooling sources such as open windows, leading to increased energy bills and unpredictable temperature changes.
Innovation Solution
A method and apparatus that monitor temperature gradients within a climate-controlled space, comparing actual gradients with expected values to detect abnormal changes, generating alerts or adjusting HVAC systems to account for unexpected heating or cooling sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If temperature monitoring and analysis systems are implemented to detect unexpected heating or cooling sources, then energy efficiency and cost savings are improved, but device complexity increases
Solution Approach 1:
The system segments the temperature monitoring function by separating data collection (temperature sensors), data processing (gradient calculation), and decision-making (threshold comparison) into distinct operational modules. This allows the complex task of energy optimization to be broken down into manageable computational steps that can be executed by existing HVAC control infrastructure.
Solution Approach 2:
The system implements feedback by continuously monitoring indoor temperature gradients, comparing them against expected values, and using this information to detect unexpected heating or cooling sources. This closed-loop feedback mechanism enables the system to automatically identify energy-wasting conditions and trigger appropriate responses without requiring complex external intervention systems.
2Reliability
If continuous temperature gradient monitoring is performed to detect abnormal changes, then reliability of climate control is improved, but use of energy increases
Solution Approach 1:
The system replaces intensive continuous physical monitoring with a computational approach that calculates temperature gradients from periodic temperature readings. Instead of requiring constant active sensing and processing, the system uses mathematical gradient analysis on sampled data, significantly reducing the energy required for monitoring while maintaining reliable detection of abnormal temperature changes.
Solution Approach 2:
The system performs partial monitoring by focusing computational resources only on calculating and analyzing temperature gradients rather than monitoring all possible environmental parameters. This selective approach provides sufficient reliability for detecting heat/cool ingress while minimizing the energy consumption associated with comprehensive environmental monitoring.
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
Effectively identifies and responds to unanticipated temperature changes, optimizing energy use and reducing utility bills by addressing sources outside the HVAC system.
Implementation Method 1
A first temperature gradient value is calculated based on the first and second indoor temperature values
Data Source
AI summary
A system and method of identifying heat/cool ingress with a climate control system. In one embodiment the method includes receiving first and second indoor temperature values that represent ambient temperature of a first climate-controlled space of a building at different times and receiving an outdoor temperature value that represents ambient temperature of an environment external to the building. A first temperature gradient value is calculated based on the first and second indoor temperature values. A first expected temperature gradient value is selected from a plurality of expected temperature gradient values stored in memory using the outdoor temperature value. A difference is determined between the first temperature gradient value and the first expected temperature gradient value. A first signal is generated if the difference between the first temperature gradient value and the first expected temperature gradient value exceeds a predetermined threshold value.