Air Conditioning Comfort Setpoint Control Using Running Mean Temperature
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing air conditioning systems struggle to balance indoor comfort and energy savings, as conventional control methods focus primarily on energy efficiency and neglect the dynamic nature of human thermal perception in varying environments.
Innovation Solution
An air conditioning device and system employing an adaptive comfort algorithm that calculates comfort temperature using exponentially-weighted running mean temperatures and regression analysis, incorporating factors like cooling/heating mode, humidity, and zone location, without requiring additional sensors beyond a temperature sensor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional temperature control methods are used, then energy saving is improved, but indoor comfort temperature control deteriorates
Solution Approach 1:
The patent implements dynamic comfort temperature control by continuously adjusting the set temperature based on outdoor temperature changes and operational time. The system transitions from static predetermined temperatures to dynamic adaptive temperatures that respond to environmental conditions, resolving the contradiction between energy saving and comfort maintenance
Solution Approach 2:
The system uses feedback from outdoor temperature sensors and operational status to continuously adjust indoor comfort temperature settings. This closed-loop control ensures that energy saving measures do not compromise indoor comfort, as the system automatically compensates for temperature changes based on real-time conditions
2Measurement precision
If additional sensors (humidity sensor, CO2 sensor, occupant detecting sensor) are installed, then measurement precision is improved, but device complexity and installation cost increase
Solution Approach 1:
The patent makes the outdoor temperature sensor serve multiple functions: it directly influences comfort temperature calculation, triggers pre-cooling/pre-heating operations, and adjusts operational timing. This multi-functional use of a single sensor achieves comprehensive environmental adaptation without requiring multiple specialized sensors
Solution Approach 2:
The system uses the air conditioner's existing operational data (running status, timing, mode) combined with outdoor temperature information to automatically determine optimal comfort temperatures. This self-service approach eliminates the need for additional sensing devices by leveraging data already available from the system's normal operation
3Measurement precision
If PMV-based control algorithms are used, then theoretical accuracy is improved, but additional devices and installation costs are required
Solution Approach 1:
The patent replaces expensive, complex PMV calculation systems requiring multiple sensors with a simple, low-cost solution using only outdoor temperature data and basic control logic. This simplified approach achieves practical comfort control without the high installation and maintenance costs of sophisticated thermal comfort systems
Solution Approach 2:
The system replaces the complex mechanical/sensor-based PMV measurement system with a computational approach using outdoor temperature data and regression-based comfort temperature calculations. This substitution maintains theoretical accuracy while eliminating the need for additional sensing hardware
Data Source
Figure 1
Figure 2
Figure 3
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.