Current rack-based cooling architecture of data centers (DCs) is a promising method since it simplifies airflow distribution and provides fast cooling regulation. Real-time on-demand control of the cooling system is an effective way to improve its operational energy efficiency without sacrificing the thermal security of IT equipment. Accurate and fast temperature distribution prediction serves as one of the bases for ensuring the superior performance of advanced control algorithms. Thus, this study proposed a novel grey-box state-space model, to rapidly predict the dynamic temperature distribution for rack-based cooling DCs. Various heat transfer physics in the rack-based cooling DCs, including heat production caused by servers and heat movements by airflows, were modeled as a state-space structure using the zonal modeling approach. The coefficient matrices were identified through the prediction-error method (PEM), in order to avoid the extremely time-consuming process of obtaining accurate physical parameters regarding the system. This developed model was validated with an experimentally validated mechanistic model and computational fluid dynamics (CFD) simulations. Additionally, the impact of the prediction horizon's size and IT workload transient changes on the proposed model's prediction accuracy were investigated as well. Through simulation, the developed model achieves sufficient accuracy with an average root mean square error (RMSE) equal to 0.19 °C and less than 3% relative error for predicting 1-min dynamic temperature evolutions. Also, the developed model shows satisfying performances for the long-horizon prediction and transient scenario, which will facilitate advanced control techniques for DC cooling systems.

当前基于机架的数据中心 (DC) 冷却架构是一种很有前途的方法，因为它简化了气流分布并提供了快速的冷却调节。冷却系统的实时按需控制是在不牺牲 IT 设备热安全性的情况下提高其运行能效的有效方法。准确、快速的温度分布预测是确保先进控制算法卓越性能的基础之一。因此，本研究提出了一种新颖的灰盒状态空间模型，以快速预测基于机架的冷却 DC 的动态温度分布。基于机架的冷却 DC 中的各种传热物理特性，包括服务器产生的热量和气流产生的热量，都使用分区建模方法建模为状态空间结构。这通过预测误差方法 (PEM) 确定系数矩阵，以避免获得有关系统的准确物理参数的极其耗时的过程。该开发模型通过实验验证的机械模型和计算流体动力学 (CFD) 模拟进行了验证。此外，还研究了预测范围的大小和 IT 工作负载瞬态变化对所提出模型的预测准确性的影响。通过仿真，所开发的模型达到了足够的精度，平均均方根误差（RMSE) 等于 0.19 °C 且预测 1 分钟动态温度演变的相对误差小于 3%。此外，所开发的模型在远期预测和瞬态场景中表现出令人满意的性能，这将促进直流冷却系统的先进控制技术。