Electronic Heating Control Using Ambient Temperature Estimation
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Solution Overview
Problem
Existing electronic devices struggle to accurately determine ambient temperature, leading to improper activation of heating control modes based on internal temperature, resulting in inefficient performance or discomfort due to premature or delayed entry into heating control modes.
Innovation Solution
The electronic device employs a sensor, communication circuit, and processor to learn scenarios, estimate ambient temperature, and adjust heating control entry points based on machine learning parameters, using GPS location, Wi-Fi signals, cell information, and external illumination to refine temperature adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the electronic device uses internal temperature to determine heating control mode, then the device can operate with simple temperature monitoring, but the heating control mode activation becomes inaccurate when ambient temperature differs from room temperature
Solution Approach 1:
The patent introduces an intermediary calculation method that uses internal temperature combined with ambient temperature difference compensation algorithms to estimate actual ambient temperature. This mediator approach allows the system to infer ambient temperature without direct sensing, resolving the contradiction between measurement accuracy and device complexity
Solution Approach 2:
The patent replaces the mechanical/physical approach of using a dedicated ambient temperature sensor with a computational approach using machine learning models. The processor learns from usage patterns and temperature data to predict ambient temperature, substituting physical sensing with intelligent algorithms to maintain accuracy while reducing hardware complexity
2Productivity
If the electronic device enters heating control mode based on fixed internal temperature threshold, then the control logic remains simple, but performance efficiency decreases when ambient temperature is higher than room temperature due to premature mode activation
Solution Approach 1:
The patent makes the heating control entry temperature dynamic rather than fixed. The processor adjusts the entry temperature threshold based on learned ambient temperature patterns and current usage scenarios. This dynamic adjustment allows the system to optimize performance efficiency by preventing premature mode activation while adapting to changing environmental conditions
Solution Approach 2:
The patent changes the parameter of heating control entry temperature from a constant value to a variable that adapts based on ambient temperature estimates and usage patterns. This parameter change enables the system to maintain optimal performance efficiency across different environmental conditions without requiring complex real-time control logic
3Measurement precision
If the electronic device uses machine learning to estimate ambient temperature and adjust heating control entry points, then temperature control accuracy improves, but device complexity increases
Solution Approach 1:
The patent performs preliminary machine learning training during device usage to establish ambient temperature estimation models before actual heating control is needed. The processor learns from accumulated temperature and usage data over time, preparing the model in advance so that when heating control is required, the system can quickly apply the pre-trained model without real-time computational complexity
Solution Approach 2:
The patent implements a self-learning system where the processor continuously improves its ambient temperature estimation accuracy by learning from its own operational data and usage patterns. The system serves itself by automatically adjusting its control parameters based on learned patterns, reducing the need for external calibration or complex manual configuration
Data Source
AI summary
An electronic device includes a sensor, a communication circuit, and a processor configured to learn a scenario based on use of the electronic device in a first temperature range, determine, using the communication circuit and/or the sensor, whether a place element of the electronic device is changed, start the scenario based on determining that the place element is changed, estimate an ambient temperature of the electronic device based on the scenario, and enter a second heating control mode at a second temperature different from a first heating control mode at a first temperature, based on the estimated ambient temperature being different from an internal temperature of the electronic device.