Experimental study and information entropy analysis on periodic performance of a PCM thermal management system for blade servers in data centers.

The high power of blade servers inside small data centers (DCs) can cause heat accumulation, which can degrade the performance of DCs. To address the problem of heat dissipation, we performed periodic experiments on a thermal management system based on a phase change material. The effects of time ratio, heating power, and cooling water temperature on the performance of thermal control and periodic stability were investigated. Information entropy reflects uncertainty by transforming a variable changes over time into a single parameter representing inhomogeneity of time. Herein, it was introduced as an evaluation index of thermal control performance. The results verified that the peak temperature of the heating surface can be maintained below 80 °C for several periods under specific conditions. Additionally, the information entropy results of the experimental data reflected the thermal control performance of the system and validated the experimental conditions. Based on the experimental results and the corresponding information entropy analysis, we proposed a design strategy for the system parameters and a method for reducing the number of measuring points. The obtained results formed the basis for the thermal management design of the server level of DCs, other electronic equipment, and electric vehicles. • Periodic performance of a PCM thermal management system is experimentally analyzed. • Information entropy evaluates the effects of system parameters on thermal control. • Design strategy and method for reducing number of measuring points are proposed. • Complex data are integrated and the periodic performance analysis is simplified. • Results can aid in designing effective thermal management systems for data centers. [ABSTRACT FROM AUTHOR]