Thermal Devices Integrated With Thermoelectric Modules With Applications to CPU Cooling

Abstract

Over the past few years, the air cooling technology improvements present diminishing returns for microprocessors cooling applications. Presently most of the proposed future cooling technologies (i.e. pumped liquid cooling or vapor compressor refrigeration) may need some fluid moving device and a large remote heat exchanger which requires additional volume. Due to the complexity, reliability issues and space requirements it is preferred to extend the air cooling within the current form factors and using passive devices. This paper will show that optimized thermoelectric modules combined with two-phase (liquid/vapor) passive devices can further improve the cooling capability compared to conventional air cooling technologies at reasonable thermoelectric cooler (TEC) power consumption. Current computational fluid dynamics programs are not yet well equipped to find out the most optimized TEC geometry (for a given COP and given thermal requirements) in a reasonable amount of computation time. Therefore, two modeling steps are proposed: find out the preliminary TEC geometry using an ID analytical program (based on uniform heat flux and a given COP) and use it as an input to CFD programs (i.e. Icepak®) for detailed predictions. Using this model, we confirmed that the conventional TEC technology must use some spreading device to dissipate the CPU heat to the TEC cold side. Different spreading devices are considered: solid metal, heat pipe, vapor chambers and single/two phase pumped cooling. Their individual performance integrated with TEC will be presented. In addition, we propose that the TEC performance to be controlled as a function of instantaneous CPU power consumption, ambient temperature and other parameters. This controller offers extra flexibility which can be used for either noise reduction or TEC power reduction. However, such power cycling of the TEC may affect the TEC reliability. Power cycling accelerated test data (>500,000 accelerated cycles) have been performed together with the life predictions will be presented in the paper.

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