Generating and implementing thermodynamic models of a structure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current HVAC control systems face challenges in accurately predicting and managing the thermal environment of structures over time due to limitations in the accuracy of thermodynamic models used for characterizing changes caused by HVAC system actuation.
Innovation Solution
A method for generating a thermodynamic model that includes determining weighting factors for predetermined basis functions, which characterize the indoor temperature trajectory of a structure in response to HVAC actuation states, using time, temperature, and HVAC actuation state information, and an intelligent network-connected thermostat that can perform these operations to improve predictive accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional thermodynamic models are used for HVAC control, then the system can operate with simple calculations, but the accuracy of predicting indoor temperature trajectory deteriorates
Solution Approach 1:
The patent segments the thermodynamic model into multiple predetermined basis functions (e.g., linear, quadratic, cubic terms) representing different temporal characteristics of temperature response. Each basis function captures a specific aspect of the temperature trajectory, allowing the complex prediction to be divided into manageable components that can be combined through weighted summation.
Solution Approach 2:
The patent implements dynamic updating of weighting factors for the basis functions based on actual measured temperature data and HVAC actuation states. This allows the model to adapt and evolve over time, improving prediction accuracy by continuously learning from operational data while maintaining a computationally efficient structure.
2Ease of operation
If simple recovery calculations are used for thermostat control, then the system is easy to operate, but the precision of temperature prediction deteriorates
Solution Approach 1:
The patent implements a self-learning mechanism where the thermodynamic model automatically updates its weighting factors using measured temperature data and HVAC actuation states from normal operation. The system serves itself by continuously improving its prediction accuracy without requiring manual recalibration or complex user intervention, maintaining ease of operation while enhancing precision.
3Measurement precision
If basic thermodynamic models are used, then energy consumption is low for model computation, but the accuracy of characterizing thermal environment changes deteriorates
Solution Approach 1:
The patent segments the temperature prediction into a set of predetermined basis functions with fixed mathematical forms. By pre-defining these basis functions, the computational energy is minimized during operation, as only the weighting factors need to be determined through simple linear combination rather than solving complex differential equations from scratch.
Solution Approach 2:
The patent performs preliminary establishment of the basis function structure before actual prediction operations. The predetermined basis functions are prepared in advance, containing all necessary mathematical formulations, so that during HVAC control operations, only lightweight weighting factor calculations are needed, significantly reducing real-time computational energy consumption.
Data Source
AI summary
In controlling the HVAC system, a need to determine an expected indoor temperature profile for a particular schedule of setpoint temperatures may arise. To make such a determination, a thermodynamic model of the structure is used. The thermodynamic model is generated by fitting weighting factors of a set of basis functions to a variety of historical data including time information, temperature information, and HVAC actuation state information. The set of basis functions characterize an indoor temperature trajectory of the structure in response to a change in HVAC actuation state, and include an inertial carryover component that characterizes a carryover of a rate of indoor temperature change that was occurring immediately prior to the change in actuation state.