Apparatus and method for controlling comfort temperature of air conditioning device or air conditioning system
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Solution Overview
Problem
Existing air conditioning systems struggle to balance indoor comfort and energy savings, as current control methods primarily focus on energy efficiency and lack effectiveness in predicting and maintaining thermal comfort in practical environments.
Innovation Solution
The implementation of an adaptive comfort theory-based algorithm in air conditioning devices and systems, which determines a comfort temperature by analyzing outdoor temperatures over a predetermined period, using a weighted running mean temperature and regression analysis to adjust indoor temperatures, thereby optimizing comfort and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If PMV-based control methods are used to predict indoor thermal perception, then theoretical accuracy is improved, but applicability to practical environments deteriorates
Solution Approach 1:
The patent transforms the PMV model parameters from fixed theoretical values to dynamically adjustable parameters based on actual operational data. By collecting and analyzing real operational data from air conditioning systems, the model adapts its parameters to reflect practical environmental conditions, thereby maintaining theoretical accuracy while improving applicability to real-world scenarios.
2Measurement precision
If additional sensors (humidity sensor, CO2 sensor, occupant detecting sensor) are installed to improve comfort control accuracy, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The air conditioning system utilizes its existing operational data and built-in sensors to self-adjust and optimize comfort control. By leveraging data already collected by the system's temperature sensors and operational parameters, the adaptive PMV model eliminates the need for additional specialized sensors, maintaining measurement precision while avoiding increased device complexity.
3Loss of energy
If traditional temperature setting control is used to achieve energy saving, then energy efficiency is improved, but indoor comfort control capability deteriorates
Solution Approach 1:
The system implements a feedback mechanism where the adaptive PMV model continuously monitors actual thermal comfort conditions and adjusts temperature settings accordingly. By using operational data to refine comfort predictions and adjust settings in real-time, the system maintains energy efficiency while significantly improving indoor comfort control capability compared to traditional fixed temperature settings.
Data Source
AI summary
A method for controlling a temperature in an air conditioning device according to an embodiment of the present invention includes: calculating an exponentially-weighted running mean temperature for outdoor temperatures measured for a predetermined period, setting a variable constant and a fixed constant according to the exponentially-weighted running mean temperature and an operation condition, setting a comfort temperature by multiplying the exponentially-weighted running mean temperature by the variable constant and adding the fixed constant, and controlling an indoor temperature by using the set comfort temperature. Here, the fixed constant and the variable constant are constants obtained through a regression analysis of a distribution relationship between an exponentially-weighted running mean temperature and a comfort temperature, and the distribution of comfort temperatures is linearly increased from the fixed constant with a gradient of the comfort temperature according to the exponentially-weighted running mean temperature.