Regression Model of Wet-Bulb Temperature in an HVAC System

  • Luping Zhuang
  • Xi ChenEmail author
  • Xiaohong Guan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 890)


It can result in substantial energy saving in heating, ventilation, and air-conditioning (HVAC) system by improving the control strategy of heating, ventilation, and air-conditioning system. However, it is challenging to obtain the optimal control strategy of an HVAC system due to its model’s complexity. In this paper, a regression model is proposed for the wet-bulb temperature which is a key variable in cooling tower and fan coil unit. The proposed model avoids the iterative computing process of obtaining the value of the wet-bulb temperature and reduces the complexity of an HVAC system’s model. Numerical results show that the proposed model takes less than 7% computing time to get the value of wet-bulb temperature, and the relative deviations are less than 0.4%, compared to the original model.


Wet-bulb temperature Regression model HVAC system 



This work was supported in part by the National Key Research and Development Program of China (2016YFB0901900 and 2017YFC0704100).


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Center for Intelligent and Networked System, Department of AutomationTsinghua UniversityBeijingChina
  2. 2.MOE KLINNS LabXi’an Jiaotong UniversityXi’anChina

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