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Energies
Volume 13
Issue 10
10.3390/en13102667
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Article

Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit

by
Hyo-Jun Kim
1,
Ji-Hyun Shin
1,
Jae Hun Jo
2 and
Young-Hum Cho
3,*
1
Department of Architectural Engineering, Graduate School of Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Korea
2
Division of Architecture, Inha University, 100 Inha-ro, Incheon 22212, Korea
3
School of Architecture, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 38541, Korea
*
Author to whom correspondence should be addressed.
Energies 2020, 13(10), 2667; https://doi.org/10.3390/en13102667
Submission received: 5 April 2020 / Revised: 10 May 2020 / Accepted: 21 May 2020 / Published: 25 May 2020
(This article belongs to the Special Issue Advances in Materials, Technologies and Controls for Sustainable Buildings)
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Abstract

Accurate measurement of air flow rate is essential in automatic building control using the variable air volume (VAV) system. In order to solve the problems of the existing air flow measurement method and improve the accuracy of air flow control, this study developed a data-based multiple regression air flow prediction model. The independent variables used in the development of the predictive model were selected as the factors used for control and monitoring when operating with variable air flow rate in the existing air conditioning system. Data collection and correlation between independent variables and air flow rate of the terminal unit were analyzed. Using the IBM SPSS statistics version 25, an air flow rate prediction model was developed using multiple regression analysis. Reliability of model was evaluated by comparing the measured airflow. The relative error of −9.3% to 10.4% is shown when comparing the estimated air flow rate by the developed model with the measured air flow rate.
Keywords: variable air volume system; terminal unit; prediction model; air flow rate; multiple regression variable air volume system; terminal unit; prediction model; air flow rate; multiple regression

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MDPI and ACS Style

Kim, H.-J.; Shin, J.-H.; Jo, J.H.; Cho, Y.-H. Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit. Energies 2020, 13, 2667. https://doi.org/10.3390/en13102667

AMA Style

Kim H-J, Shin J-H, Jo JH, Cho Y-H. Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit. Energies. 2020; 13(10):2667. https://doi.org/10.3390/en13102667

Chicago/Turabian Style

Kim, Hyo-Jun, Ji-Hyun Shin, Jae Hun Jo, and Young-Hum Cho. 2020. "Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit" Energies 13, no. 10: 2667. https://doi.org/10.3390/en13102667

APA Style

Kim, H.-J., Shin, J.-H., Jo, J. H., & Cho, Y.-H. (2020). Development of Air Flow Rate Prediction Model Using Multiple Regression in VAV Terminal Unit. Energies, 13(10), 2667. https://doi.org/10.3390/en13102667

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