Durham School of Architectural Engineering and Construction
Date of this Version
Santiwattana, K. (2016). An Investigation of DX Cooling Coil Inherent Characteristics. University of Nebraska-Lincoln.
DX cooling coil (DCC) systems have dominated light commercial and household applications in the U.S for several decades. Approximately 14.5% of energy use is consumed by space cooling in commercial buildings, whereas 87% of households are installed with air-conditioners. Improper installation, poor design, and lack of optimized control/operations incur faults in HVAC systems causing 25% to 50% energy waste in a building. These consequences are subject to inefficient equipment modelling of which is developed from: (1) insufficient understanding in equipment characteristics, (2) uncertainties in testing environment and data, and (3) access and cost limitations. Therefore, in this thesis DCC inherent characteristics are investigated by using manufacturers’ data to improve DCC modelling procedures.
Model based control/optimization of DCC methods are: white-box (theoretical-based and physical-based), requiring particular equipment physical geometries, and black-box (empirical-based), requiring high-qualitied data for performance mapping. In practice, physical geometries and laboratory testing data are not always available or not accurate enough to provide robust approximations and validations. A generic rating-data-based (GRDB) model, which can accurately predict roof top unit (RTU) capacities, is derived from readily available manufacturers’ data, and the model format is based on measured environment temperatures and air flow rates (CFM). Accordingly, GRDB will be re-examined and extensively applied to mini-split heat pumps (MSHPs). Unlike RTUs, MSHPs’ manufacturing performance data ranges are limited, so intensive understanding of DCC inherent characteristics are essential to create more accurate models. In accordance, the characteristics are examined by air principles and fundamentals of vapor compression cycle (VCC), and illustrated by normalized capacities (NCAPs) and sensible heating ratio (SHR) plots. In addition, new DCC modelling procedures are proposed in this research.
Finally, the improved GRDB for MSHPs, validated by laboratory data, shows relative errors ranged from 12.5% to -8.6%. In addition, the proposed inherent characteristic hypotheses are validated using manufacturers’ data from various conditions and systems. The results show correlations in associated with proposed hypotheses. Profound understanding of DCC inherent characteristics in this research could lead to better modelling procedures as it could lessen model complexity and computational processes, which could benefit low-cost sensing and fault detection and diagnostics technologies.
Advisor: Haorong Li
A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Architectural Engineering, Under the Supervision of Professor Haorong Li. Lincoln, Nebraska: December, 2016
Copyright 2016 Krittima Santiwattana