Method for controlling refrigerator operation and refrigerator
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Solution Overview
Problem
Current refrigerator control algorithms do not adequately consider consumer habits and preferences, leading to inefficient temperature control, increased energy consumption, and reduced food freshness due to inadequate processing of parallel events influencing refrigeration operation.
Innovation Solution
A method that uses a door opening sensor to monitor and analyze door opening patterns, generating a probability distribution to adjust the cooling system's operation, including defrost timing and energy usage, and employs a support vector machine to detect thermal load insertions, optimizing temperature stability and energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If current control algorithms apply the same logic to determine compressor and fan speeds regardless of time of day, then temperature control is maintained, but noise level increases during rest hours and energy consumption is not optimized
Solution Approach 1:
The control algorithm dynamically adjusts compressor and fan speeds based on the time of day, transitioning from static same-logic control to adaptive control that considers whether it is day or night, thereby reducing noise during rest hours while maintaining temperature control
Solution Approach 2:
The system changes operational parameters (compressor speed, fan speed) based on temporal conditions (time of day), implementing different control strategies for daytime and nighttime to optimize both temperature maintenance and noise reduction
2Device complexity
If control algorithms do not consider consumer habits and preferences, then device complexity is reduced, but temperature consistency deteriorates and food preservation is impacted
Solution Approach 1:
The control system incorporates feedback from door opening sensors and usage patterns to learn consumer habits and preferences, using this information to adjust control strategies and improve temperature consistency while maintaining reasonable algorithm complexity
Solution Approach 2:
The refrigerator system automatically learns and adapts to user behavior patterns without requiring manual programming, implementing self-service adaptation that improves temperature consistency based on observed usage habits
3Device complexity
If door opening patterns are not monitored and analyzed, then device complexity is lower, but temperature stability deteriorates and energy consumption increases
Solution Approach 1:
The system performs preliminary analysis of door opening patterns to predict thermal load insertions before they occur, enabling proactive adjustment of cooling operations to maintain temperature stability and reduce energy consumption
Solution Approach 2:
Door opening sensors serve as intermediaries that provide information about user behavior, which the control algorithm processes to infer thermal load events and adjust cooling operations accordingly
4Device complexity
If thermal load insertions are not detected, then device complexity is reduced, but temperature control efficiency deteriorates and energy consumption increases
Solution Approach 1:
The system replaces direct thermal measurement with indirect detection methods using door opening sensor data and control algorithm analysis to identify thermal load insertions, reducing the need for additional complex sensing hardware while improving energy control efficiency
Data Source
AI summary
Method (100) for controlling the operation of a refrigerator (1) comprising: a cabinet (2) defining a refrigeration and/or freezing area; an isolating door (3) that opens and closes the refrigeration and/or freezing area of the cabinet (2); a door opening sensor (31); and a cooling system (5) configured to modify the temperature of the refrigeration and/or freezing area; the method (100) comprising the steps of: monitoring the opening and closing of the door (31) by means of the door opening sensor (31) during a determined period; generating (206) a door opening probability distribution (206a) at the time monitored in the previous step; and maintaining or modifying the operation of the cooling system (5) according to the door opening probability distribution (206a).


