Predictive Thermal Control for Electronic Devices
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Solution Overview
Problem
Existing temperature control methods for electronic devices are reactive, invoking cooling measures based on current temperature, which can disrupt user experiences by triggering cooling actions at inconvenient times, such as during video conferences or gaming.
Innovation Solution
A predictive control system that anticipates future user tasks by analyzing past behavior and power usage patterns, allowing for preemptive cooling operations to maintain optimal performance and user experience without interrupting device usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If reactive cooling measures are invoked based on current temperature, then temperature control is achieved, but user experience is disrupted by cooling actions at inconvenient times
Solution Approach 1:
The system performs preliminary cooling actions before the device temperature reaches thresholds that would trigger reactive cooling. By analyzing historical usage patterns and predicting future high-power tasks, the system proactively reduces temperature during low-usage periods, ensuring cooling measures are already in place before they would be needed, thus avoiding disruption to user activities.
Solution Approach 2:
The system applies preliminary anti-action by implementing cooling measures in advance to prevent the harmful effect of high temperature before it occurs. By predicting future thermal conditions based on historical data and scheduling cooling during appropriate times, the system counteracts potential temperature rises before they disrupt user experience.
2Temperature
If cooling measures are applied to reduce temperature, then temperature control is improved, but device performance may be reduced due to preemptive operations
Solution Approach 1:
The system performs preliminary cooling during periods of low predicted power usage, before high-power tasks are scheduled to run. By analyzing historical patterns to identify optimal cooling windows, the system applies cooling measures when they will have minimal impact on overall device productivity, ensuring performance is maintained during critical tasks while still achieving temperature control.
Solution Approach 2:
The system dynamically adjusts cooling intensity and timing based on predicted power usage patterns and task schedules. By making cooling operations adaptive rather than static, the system optimizes the balance between temperature control and performance maintenance, applying stronger cooling during low-usage periods and reducing cooling during high-performance requirements.
Data Source
AI summary
Systems and methods are disclosed for determining a current machine state of a processing device, predicting a future processing task to be performed by the processing device at a future time, and predicting a list of intervening processing tasks to be performed by a first time (e.g. a current time) and the start of the future processing task. The future processing task has an associated initial state. A feed-forward thermal prediction model determines a predicted future machine state at the time for starting the future processing task. Heat mitigation processes can be applied in advance of the starting of the future processing task, to meet the future initial machine state for starting the future processing task.