Design and Optimization of Control Strategy to Reduce Pumping Power in Dynamic Liquid Cooling

Abstract Data centers are a large group of networked servers used by organizations for computational and storage purposes. In 2014, data centers consumed an estimated 70 billion kWh in the United States alone. It is incumbent on thermal engineers to develop efficient methods in order to minimize the expenditure at least toward cooling considering the limited available power resources. One of the key areas where electronic cooling research has been focusing, is addressing the issue of nonuniform power distribution at the rack, server and even at package levels. Nonuniform heating at the chip level creates hotspots and temperature gradients across the chip which in turn significantly increases the cost of cooling, as cooling cost is a function of the maximum junction temperature. This challenge has increased the use of temperature sensing mechanisms to help in finding ways to mitigate the gradients. A very effective way to conserve pumping power and address hotspots on the single or multichip modules is by targeted delivery of liquid coolant. One way to enable such targeted delivery of coolant is by using dynamic cold plates coupled with self-regulating flow control device that can control flow rate based on temperature. This novel technology will have more effective implementation coupled with a good control strategy. This paper addresses the development and testing of such control strategy with minimal sensors along with less latency and optimization of the same.