Fine-grain dynamic solid-state cooling system
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Solution Overview
Problem
Traditional solid-state cooling systems, such as thermoelectric coolers, are inefficient in power-constrained environments and struggle to effectively dissipate heat from high-performance computing components like CPUs and GPUs, limiting their ability to maintain low temperatures and increasing waste heat dissipation.
Innovation Solution
A fine-grain dynamic solid-state cooling system is developed, combining advanced solid-state cooling units with a sensor grid and a micro-controller optimizer, using Pyrolytic Carbon (PyC) for efficient heat transfer and data-driven optimization to dynamically adjust cooling power across multiple sub-regions of a heat source, enhancing heat dissipation efficiency and reaching temperatures below -160°C.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional solid-state cooling systems are used, then the structure is simple, but the heat dissipation efficiency is low and waste heat increases
Solution Approach 1:
The cooling system is divided into multiple independently controllable cooling sub-units arranged in a grid pattern, each corresponding to specific sub-regions of the heat source. This segmentation allows targeted cooling of high-heat areas while leaving low-heat areas untouched, significantly improving heat dissipation efficiency without requiring complete system overhaul.
Solution Approach 2:
The system applies different cooling intensities to different spatial locations based on local heat generation characteristics. The controller dynamically adjusts the power supplied to each cooling sub-unit based on real-time temperature feedback from corresponding sensor sub-units, ensuring optimal cooling efficiency for each specific region rather than uniform cooling across the entire heat source.
2Use of energy by moving object
If traditional solid-state cooling systems are used, then the power consumption is high, but the cooling capability is insufficient
Solution Approach 1:
The system dynamically adjusts the operating state of each cooling sub-unit based on real-time thermal conditions. The controller continuously monitors temperature via sensor sub-units and modulates the power supply to cooling sub-units accordingly, transitioning between different power states to match the actual cooling demand, thereby reducing overall power consumption while maintaining adequate cooling capability.
Solution Approach 2:
The system incorporates sensor sub-units that provide real-time temperature feedback from the heat source surface to the controller. This feedback loop enables the controller to make informed decisions about power distribution to cooling sub-units, adjusting power consumption based on actual thermal conditions rather than operating at fixed high power levels, thus achieving better cooling capability per unit of energy consumed.
3Loss of energy
If dynamic power adjustment is implemented, then the heat dissipation efficiency improves, but the system complexity increases
Solution Approach 1:
The system merges the functions of temperature sensing and cooling control into an integrated grid structure where sensor sub-units and cooling sub-units are spatially correlated and controlled by a single controller. This integration reduces the complexity that would otherwise arise from separate sensing and actuation systems, as the one-to-one correspondence between sensor and cooling sub-units simplifies the control architecture while enabling dynamic power adjustment for improved heat dissipation 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
The system achieves nearly 60% efficiency in heat dissipation, allowing it to compete with extreme cooling solutions, and enables the use of solid-state superconducting devices by optimally managing heat across spatial and temporal dynamics, effectively cooling critical components in high-performance computing and other temperature-sensitive applications.
Implementation Method 1
One type of solid-state heat pump is a thermoelectric cooler, which operates by the Peltier effect or thermoelectric effect. The thermoelectric cooler has two sides and when an electric current flows through the device, it brings heat from one side to the other so that one side gets cooler while the other gets hotter.
Implementation Method 2
The heat exchanger thermally connects to the hot side of each of the solid-state cooling sub-units and is configured to dissipate additional heat from the sub-regions of the heat source and waste heat generated from powering the solid-state cooling sub-units.
Implementation Method 3
A plurality of sensor sub-units arranged in a grid and configured to be thermally connected to a heat source
Data Source
AI summary
A cooling system includes a controller, a plurality of sensor sub-units, a plurality of solid-state cooling sub-units and a heat exchanger. The sensor sub-units are configured to be thermally connected to a heat source. The heat source has a plurality of sub-regions that correspond with each of the sensor sub-units. Each solid-state cooling sub-unit corresponds with and thermally connects to one of the sensor sub-units and is configured to dissipate heat from the sub-regions of the heat source. The heat exchanger is configured to dissipate heat from the sub-regions of the heat source and waste heat. The controller, based on temperatures sampled from the plurality of sensor sub-units and predictions made by an optimizer, is configured to determine the one or more sub-regions of the heat source to cool.