TY - JOUR
T1 - Grey-box models of chiller evaporator for practical integration in building automation systems
AU - Dou, Hongwen
AU - Zhang, Kun
AU - Zmeureanu, Radu
N1 - Publisher Copyright:
© Copyright © 2025 ASHRAE.
PY - 2026
Y1 - 2026
N2 - This paper presents the development and validation of grey-box models for estimating the chilled water temperature difference ΔTchw across the chiller evaporator, with potential applications as virtual sensors in building automation systems (BAS) or integration into other mathematical models. The models are established for two scenarios, variable and constant chilled water flow rates under quasi-steady-state operation. These models require a small number of input variables and are characterized by strong adaptability. Three case studies of different chillers are used to validate the proposed virtual sensors with both static and dynamic windows methods, and help in the generalization of the proposed method. The models demonstrate high accuracy and robustness, achieving a root-mean-squared error of 0.19 °C in one case study. This study addresses the gap in the availability of simple yet reliable models that can be practically integrated into building automation systems for virtual sensing, virtual calibration, fault detection and diagnosis, and HVAC system control and optimization.
AB - This paper presents the development and validation of grey-box models for estimating the chilled water temperature difference ΔTchw across the chiller evaporator, with potential applications as virtual sensors in building automation systems (BAS) or integration into other mathematical models. The models are established for two scenarios, variable and constant chilled water flow rates under quasi-steady-state operation. These models require a small number of input variables and are characterized by strong adaptability. Three case studies of different chillers are used to validate the proposed virtual sensors with both static and dynamic windows methods, and help in the generalization of the proposed method. The models demonstrate high accuracy and robustness, achieving a root-mean-squared error of 0.19 °C in one case study. This study addresses the gap in the availability of simple yet reliable models that can be practically integrated into building automation systems for virtual sensing, virtual calibration, fault detection and diagnosis, and HVAC system control and optimization.
UR - https://www.scopus.com/pages/publications/105024767490
U2 - 10.1080/23744731.2025.2593799
DO - 10.1080/23744731.2025.2593799
M3 - Journal Article
AN - SCOPUS:105024767490
SN - 2374-4731
VL - 32
SP - 263
EP - 280
JO - Science and Technology for the Built Environment
JF - Science and Technology for the Built Environment
IS - 2
ER -