Abstract
Recently, saving the cooling power in servers by controlling the fan speed has attracted considerable attention because of the increasing demand for high-density servers. This paper presents an optimal self-tuning proportional-integral-derivative (PID) controller, combining a PID neural network (PIDNN) with fan-power-based optimization in the transient-state temperature response in the time domain, for a server fan cooling system. Because the thermal model of the cooling system is nonlinear and complex, a server mockup system simulating a 1U rack server was constructed and a fan power model was created using a third-order nonlinear curve fit to determine the cooling power consumption by the fan speed control. PIDNN with a time domain criterion is used to tune all online and optimized PID gains. The proposed controller was validated through experiments of step response when the server operated from the low to high power state. The results show that up to 14% of a server’s fan cooling power can be saved if the fan control permits a slight temperature response overshoot in the electronic components, which may provide a time-saving strategy for tuning the PID controller to control the server fan speed during low fan power consumption.
Highlights
The rapid growth in information technology has contributed to the high demand for commercial servers, making power consumption by the cooling fans a major concern in server design
This study focused on PID neural network (PIDNN) self-tuning because of its simple structure and nonlinear learning ability [13]
The program was loaded into the NI sbRIO-9602, which integrates a real-time processor, a user-reconfigurable field-programmable gate array (FPGA), and input and output (I/O) ports
Summary
The rapid growth in information technology has contributed to the high demand for commercial servers, making power consumption by the cooling fans a major concern in server design. Commercial servers are commonly equipped with multiple CPU sockets and densely housed to execute network applications. High-density servers have a high likelihood of thermal failure, and require additional power consumption for cooling. Lefurgy et al [1] indicated that fan power can reach up to 51% of the overall server power budget. Some studies [2,3] have indicated that an additional 0.5–1 W of power is required for the cooling equipment for every 1 W of power used for operating a single server. Fan power efficiency improvement attracts increasing attention as the demand for high-density servers increases
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