AI Air Conditioner Mode Switching for Adaptive Comfort Control
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Solution Overview
Problem
Conventional air conditioner control systems have limitations in dynamically reflecting changes in external temperature, humidity, and occupancy, leading to suboptimal operation modes that do not fully consider varying environmental conditions.
Innovation Solution
An air conditioner system utilizing a machine-learning network to generate parameters for controlling operation modes, including wind direction and air volume, based on real-time data from indoor and outdoor units, switching between rapid and comfortable modes to maintain target temperatures with reduced energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the air conditioner operates in a single fixed operation mode, then the control system is simple, but it cannot dynamically adapt to changing environmental conditions such as temperature, humidity, and occupancy
Solution Approach 1:
The patent implements dynamic operation modes that automatically switch between first and second modes based on real-time environmental conditions. The control system transitions from static to dynamic operation, adjusting cooling/heating parameters according to changing temperature, humidity, and occupancy levels detected by sensors.
Solution Approach 2:
The air conditioner performs self-diagnosis and automatic mode selection based on environmental feedback. The system monitors its own operation status and environmental parameters, then autonomously determines the appropriate operation mode without requiring manual user intervention or complex external control.
2Use of energy by moving object
If the air conditioner uses a single operation mode, then the device complexity is low, but the energy consumption efficiency is suboptimal under varying conditions
Solution Approach 1:
The patent changes operational parameters by switching between two distinct operation modes with different cooling/heating capabilities. The first mode operates with higher capacity for rapid temperature adjustment, while the second mode uses lower capacity for energy-efficient maintenance, optimizing energy consumption based on actual environmental needs.
Solution Approach 2:
The control system periodically evaluates environmental conditions and switches between operation modes at appropriate intervals. This periodic monitoring and switching ensures the system maintains optimal energy efficiency by adapting to changing conditions rather than operating continuously in a fixed mode.
3Measurement precision
If the air conditioner switches between two operation modes with different temperature change rates, then temperature control precision is improved, but the control complexity increases
Solution Approach 1:
The patent segments the operation into two distinct modes: a first mode for rapid temperature adjustment with higher temperature change rates, and a second mode for precise temperature maintenance with lower change rates. This segmentation allows the system to apply different control strategies appropriate for each operational phase, improving overall temperature control precision.
Solution Approach 2:
The control system continuously monitors temperature, humidity, and occupancy parameters, using this feedback to determine when to switch between operation modes. The feedback mechanism enables precise temperature control by adjusting the operation mode based on the current deviation from the target temperature and environmental conditions.
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
The system efficiently determines optimal operation modes by using generated parameters, allowing for precise temperature control and reduced energy usage by switching between modes based on current conditions, maintaining comfort while minimizing power consumption.
Implementation Method 1
the supplied refrigerant exchanges heat with the air before the air is discharged from the blowing unit
Data Source
AI summary
An air conditioner includes: an indoor unit including a blowing unit to discharge air; an outdoor unit supplying compressed refrigerant to the indoor unit, to exchange heat with the air before discharge. The air conditioner also includes at least one computer memory operably connectable to at least one processor and storing instructions that, when executed, perform operations that include: generating at least one parameter in a first operation mode, which is operated only within a preset time range; controlling, based on an operation mode information, at least one of (i) the blowing unit to change a wind direction and an air volume, or (ii) the outdoor unit; and switching to a second operation mode after a time period of operation in the first operation mode. The operation mode information includes at least one result factor obtained from at least one machine-learning network.