Dynamic Load Scheduling for Thermal Management
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Solution Overview
Problem
Existing cooling mechanisms for electronic components often require large heat sinks to manage peak loads, leading to increased size and cost, while also limiting the ability to provide surge processing without overheating.
Innovation Solution
A computing device with a temperature sensor and controller that generates a load schedule for electronic components based on current and anticipated temperatures, allowing for dynamic adjustment of power usage to prevent overheating, even during peak loads, by throttling or shutting down subsystems and adjusting CPU speed, battery charge rate, and amplifier power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large heat sinks are used to manage peak loads, then the ability to provide surge processing without overheating is improved, but the size and cost of the cooling system increases
Solution Approach 1:
The patent implements dynamic load scheduling that adjusts electronic component operation based on real-time temperature monitoring and predicted workload. The system dynamically throttles or shuts down subsystems during high-temperature periods while allowing full performance during cooler periods, replacing the static requirement for oversized heat sinks with an adaptive control approach.
Solution Approach 2:
The system performs preliminary temperature assessment and workload prediction before processing demands arise. By monitoring temperature trends and predicting future thermal states, the load scheduler proactively adjusts component operation to prevent overheating before it occurs, rather than reacting after temperature thresholds are exceeded.
2Temperature
If large heat sinks are used to manage peak loads, then thermal management capability is improved, but the cost of the cooling system increases
Solution Approach 1:
The patent replaces static thermal management hardware with dynamic software-based load scheduling. The system continuously monitors temperature and predicts future thermal states, then dynamically adjusts component operation to maintain thermal safety margins. This approach achieves the same thermal management capability as large heat sinks but with smaller, less expensive cooling components.
Solution Approach 2:
The system changes operational parameters (load levels, power consumption) of electronic components based on thermal conditions. By dynamically adjusting these parameters rather than relying on fixed thermal capacity hardware, the system achieves effective thermal management with reduced heat sink size and lower overall cooling system cost.
3Use of energy by moving object
If the heat sink operates near maximum temperature, then power usage efficiency is improved, but the lifespan of electronic components decreases
Solution Approach 1:
The patent implements a feedback-based load scheduling system that continuously monitors temperature and adjusts component operation accordingly. The load scheduler receives temperature feedback, predicts future thermal states, and modifies load distribution to maintain temperatures below thresholds that would compromise component lifespan, while still maximizing power efficiency within safe operating margins.
Solution Approach 2:
The system takes preliminary protective action by monitoring temperature trends and predicting when thermal thresholds would be exceeded. Before components reach dangerous temperatures, the load scheduler proactively reduces load on affected subsystems, preventing thermal stress that would reduce component lifespan while maintaining efficient operation during safe temperature ranges.
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 smaller, more cost-effective heat sinks while allowing for brief surges in processing power without overheating, extending the lifespan of electronic components and optimizing power usage.
Implementation Method 1
heat sinks are typically coupled with electronic components and dissipate heat via conduction to the heat sink
Implementation Method 2
dissipate heat via conduction to the heat sink and then via radiation and convection to the surroundings
Implementation Method 3
dissipate heat via conduction to the heat sink and then via radiation and convection to the surroundings
Data Source
AI summary
The disclosed computing device may include electronic components, at least one of which is a processor. The computing device may also include a heat sink thermally coupled to the electronic components, as well as a temperature sensor that determines the current temperature inside the computing device. The computing device may further include a controller. The processor may generate a load schedule for the electronic components based on the current temperature inside the computing device. This load schedule ensures that a maximum temperature for the heat sink is not exceeded even when the total system power load exceeds, for a short period of time, the maximum sustainable power level the heat sink can dissipate. The controller may then load the electronic components according to the generated load schedule. Various other methods, systems, and computer-readable media are also disclosed.