Virtual Thermal Sensor Using Energy Flow for Heat Prediction
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Solution Overview
Problem
Conventional temperature monitoring in handheld and wearable devices relies on internal sensors, which provide limited insights into thermal dynamics across the device, leading to inaccurate heat planning and inefficient thermal management due to their instantaneous measurements and lack of historical state or rate of change capture.
Innovation Solution
The integration of cumulative energy flow data from dedicated accumulators and sensors to predict internal and external temperatures by tracking energy transformations into heat, light, and radio waves, allowing for more sophisticated thermal management based on ambient conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If internal temperature sensors are used for monitoring, then temperature measurement is provided, but thermal dynamics insight is limited and heat planning accuracy deteriorates
Solution Approach 1:
The patent introduces an intermediary computational model that processes sensor data to infer thermal dynamics. Instead of relying solely on direct sensor measurements, the system uses a thermal model as an intermediary to calculate heat generation, heat dissipation, and temperature trends, thereby recovering lost thermal dynamics information while maintaining measurement functionality.
Solution Approach 2:
The patent creates a virtual copy of the thermal system through computational modeling. By simulating thermal behavior in software, the system generates a virtual representation of temperature dynamics that complements physical sensor data, enabling comprehensive thermal analysis without additional hardware sensors.
2Measurement precision
If internal temperature sensors are used, then instantaneous temperature is measured, but historical state and rate of change capture are lost
Solution Approach 1:
The patent performs preliminary computational actions by continuously running thermal models that predict future temperature states based on historical data. The system proactively calculates thermal trends and prepares thermal management decisions before actual overheating occurs, utilizing accumulated historical state information to anticipate future conditions.
Solution Approach 2:
The patent implements feedback mechanisms where thermal model predictions are continuously compared with actual sensor measurements. This feedback loop refines the computational model over time, improving accuracy of historical state reconstruction and enabling better prediction of temperature rate of change based on past thermal behavior patterns.
3Device complexity
If conventional temperature monitoring is used, then simple sensing is provided, but thermal management efficiency deteriorates
Solution Approach 1:
The patent enables the thermal management system to serve itself through autonomous computational modeling. The thermal model automatically processes sensor data, predicts temperature trends, and generates management decisions without requiring complex external control systems, thereby improving thermal management efficiency while maintaining relatively simple system architecture.
Solution Approach 2:
The patent transforms the approach by changing from direct temperature control to indirect thermal management through computational parameters. Instead of reacting to temperature readings alone, the system manipulates thermal model parameters such as heat generation rates, thermal conductivity estimates, and ambient temperature predictions to optimize thermal management efficiency.
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
This approach enables accurate prediction of temperature changes and enhances thermal management by accounting for cumulative energy flow, reducing the need for frequent software wakeups and improving thermal headroom estimation.
Implementation Method 1
detecting an amount of energy being discharged from a battery of a computing device
Implementation Method 2
predict, based on the amount of energy being discharged from the battery, a thermal response of the computing device
Data Source
AI summary
The disclosed computer-implemented method may include detecting an amount of energy being discharged from a battery of a computing device. The method may further include predicting, based on the amount of energy being discharged from the battery, a thermal response of the computing device. Furthermore, the method may include performing thermal management of the computing device based on the predicted thermal response. Various other methods, systems, and computer-readable media are also disclosed.