Multi-Node Fan Duty Control via Signal Ranking
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Solution Overview
Problem
Modern computing devices generate excessive heat due to powerful electronic components, leading to potential physical damage and system failures, and existing cooling fan control methods are inefficient, prone to errors, and wasteful in energy.
Innovation Solution
A logic controller, such as a complex programmable logic device (CPLD), is used to regulate fan duty by receiving and ranking control signals from multiple computing nodes, selecting the highest fan duty request, and adjusting the speed of cooling fans to maintain optimal temperature ranges, allowing for flexible and efficient cooling across multiple thermal zones.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If fan speed is increased to remove excessive heat, then cooling effectiveness is improved, but energy consumption increases and overcooling occurs
Solution Approach 1:
The patent implements dynamic fan speed adjustment by continuously monitoring temperature sensors and modifying fan duty cycles in real-time. The control system transitions from static to dynamic operation, allowing fans to accelerate or decelerate based on thermal conditions, thereby optimizing cooling effectiveness while minimizing energy consumption.
Solution Approach 2:
The system employs feedback control mechanisms where temperature sensors continuously monitor thermal conditions and feed this information back to the control logic. The controller adjusts fan speed based on this feedback, creating a closed-loop system that prevents overcooling and energy waste while ensuring adequate cooling when needed.
2Use of energy by moving object
If fan speed is decreased to save energy, then power efficiency is improved, but cooling effectiveness deteriorates and overheating occurs
Solution Approach 1:
The control system dynamically adjusts fan speed to match actual thermal demands, allowing the system to operate at lower power consumption levels during moderate thermal conditions while maintaining adequate cooling. The dynamic adjustment ensures cooling effectiveness is preserved when needed without constant high-speed operation.
Solution Approach 2:
The system changes operational parameters (fan duty cycle, speed) based on thermal conditions. By monitoring temperature and adjusting fan parameters accordingly, the system achieves power efficiency during normal operation while maintaining cooling effectiveness when thermal thresholds are approached.
3Measurement precision
If multiple control signals from multiple computing nodes are processed to determine optimal fan duty, then thermal management accuracy is improved, but control complexity increases
Solution Approach 1:
The control system segments the multi-node thermal management problem by processing control signals from different computing nodes separately and then integrating them through a ranking mechanism. This segmentation approach maintains thermal management accuracy for each node while simplifying the overall control logic through modular signal processing.
Solution Approach 2:
The control system introduces an intermediary ranking mechanism that processes multiple control signals from different computing nodes. This intermediary layer ranks signals based on thermal urgency and selects appropriate fan duty levels, simplifying the control complexity while maintaining accurate thermal management across all nodes.
4Reliability
If fan duty is increased to prevent overheating, then system reliability is improved, but energy waste increases due to overcooling
Solution Approach 1:
The system uses feedback control to adjust fan duty based on actual thermal conditions, preventing both overheating and overcooling. Temperature sensors provide continuous feedback to the control logic, which modulates fan speed to maintain temperatures within safe ranges, ensuring system reliability while minimizing energy waste from unnecessary high-speed operation.
Solution Approach 2:
The control system dynamically changes fan duty parameters based on thermal conditions, transitioning from fixed high-duty operation to variable duty cycles. This parameter adjustment ensures system reliability by maintaining adequate cooling while reducing energy waste through optimized fan operation during moderate thermal 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
This approach enables effective and efficient thermal management by optimizing fan control, reducing the risk of overheating or overcooling, and improving power efficiency by dynamically adjusting fan speeds based on actual thermal needs.
Implementation Method 1
Cooling fans are widely utilized to remove heat from computing devices by actively exhausting accumulated hot air
Data Source
AI summary
Embodiments generally relate to thermal management in a multi-node computing device. The present technology discloses techniques that can receive multiple control signals from multiple computing nodes, each of the control signals being associated with a fan duty request, which is a request for a fan duty needed to keep a related computing node operating within a predetermined temperature range. The logic controller can rank the received control signals and select a control signal that requests a highest fan duty; lastly, the logic controller can cause multiple cooling fans to operate at the selected highest fan duty.