Refrigerator and method for controlling refrigerator with improved cooling management
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Solution Overview
Problem
Existing refrigerator technologies fail to effectively adjust the storage space temperature based on the type and quantity of items placed, leading to suboptimal conditions and inefficient cooling.
Innovation Solution
A refrigerator system that uses a pre-trained machine learning-based overload item determination model to identify items placed in the storage space and adjusts the compressor's operation to maintain optimal temperature, predicting door opening and closing patterns to preemptively adjust the temperature and enter a sleep mode during extended periods of inactivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the refrigerator uses conventional cooling control without item recognition, then the device complexity is low, but the temperature control precision deteriorates when overload items are placed
Solution Approach 1:
The patent replaces conventional mechanical temperature sensing with a machine learning-based overload item determination model that uses camera imaging and image processing to identify items and predict their cooling impact, thereby improving temperature control precision without relying solely on physical temperature sensors
Solution Approach 2:
The patent introduces an intermediary machine learning model that acts between the camera system and the temperature control system, processing image data to determine overload items and generate appropriate cooling control signals, thus bridging the gap between visual recognition and thermal management
2Stability of the object's composition
If the refrigerator quickly responds to temperature changes by continuous compressor operation, then the temperature stability improves, but the energy consumption increases
Solution Approach 1:
The patent applies preliminary action by using the machine learning model to predict temperature changes before they occur based on item recognition, allowing the compressor to be adjusted in advance according to the predicted cooling load, thus maintaining temperature stability while avoiding unnecessary continuous operation
Solution Approach 2:
The patent implements dynamic compressor control by adjusting the compressor operation based on real-time item recognition results and predicted temperature changes, rather than maintaining a fixed operation mode, thereby optimizing the balance between temperature stability and energy consumption
3Measurement precision
If the refrigerator determines overload items by monitoring temperature changes over time, then the measurement precision improves, but the response time deteriorates
Solution Approach 1:
The patent replaces time-based temperature monitoring with image-based item recognition using a camera and machine learning model, allowing immediate identification of overload items upon placement without waiting for temperature changes to manifest, thus improving response time while maintaining determination precision
Solution Approach 2:
The patent applies preliminary action by capturing images of items as they are placed in the storage space and processing them through the machine learning model before significant temperature changes occur, enabling early detection and immediate response to overload 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
Improves cooling efficiency, maintains optimal storage conditions, and reduces energy consumption by quickly identifying overload items and adjusting the compressor's operation based on item type and quantity, as well as anticipating door usage patterns.
Implementation Method 1
the refrigerator is configured to cool the inside of the storage space by using cooling air which is generated through heat exchange with refrigerants circulating in a refrigeration cycle
Data Source
AI summary
A refrigerator can include a storage compartment having a storage space and an opening; at least one door coupled to the storage compartment to open and close a part of the storage compartment; a compressor configured to provide the storage compartment with freezing capacity or cooling capacity; a processor configured to control driving of the compressor; and a memory operably connected to the processor and configured to store code to cause the processor to in response to recognizing placement of an item in the storage space, determine whether the item is an overload item to generate a determination result; and control the driving of the compressor to adjust a temperature of the storage space based on the determination result.