A Tool for Evaluating Fault Detection and Diagnostic Methods for Fan Coil Units

Published

December 6, 2016

Author(s)

Shokouh Pourarian, Jin Wen, Daniel Veronica, Amanda Pertzborn, Xiaohui Zhou, Ran Liu

Abstract

Dynamic simulation software tools are needed for the research and development of improved methods for automatic control and automated fault detection and diagnosis of heating, ventilation, and air conditioning (HVAC) systems. These tools must generate data that accurately simulate the real data that instruments would record from both fault-free and faulty dynamic operation of HVAC systems and equipment. Fan coil units (FCU) are simple, economical devices used extensively in the HVAC systems of commercial, institutional and multifamily residential buildings. However, very little has been reported in the literature to improve their design and operation. There has also been a lack of dynamic simulation tool development focusing on FCUs. The work here develops a tool to simulate data from FCUs operating dynamically under faulty and fault-free conditions. A comprehensive and systematic validation procedure, using data collected experimentally from real FCUs in a laboratory, is used to validate the tool under both faulty and fault-free operating conditions in different seasons. The validated tool not only predicts real-world FCU behavior under different control strategies, but it also predicts symptoms associated with various faults, as well as the effects those faults have on system performance and occupant comfort.

Citation

Energy and Buildings

Volume

136

Pub Type

Journals

Download Paper

https://doi.org/10.1016/j.enbuild.2016.12.018

Local Download

Keywords

Fan Coil Unit, Simulation, Fault-free and faulty conditions, AFDD

Citation

Pourarian, S. , Wen, J. , Veronica, D. , Pertzborn, A. , Zhou, X. and Liu, R. (2016), A Tool for Evaluating Fault Detection and Diagnostic Methods for Fan Coil Units, Energy and Buildings, [online], https://doi.org/10.1016/j.enbuild.2016.12.018, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=919235 (Accessed October 1, 2025)