Session: 08-04-02: Sustainable Energy Systems for Heating and Cooling

Paper Number: 111611

111611 - A Literature Review of Automated Fault Detection and Diagnostics for HVAC Systems 

Modern Air-Conditioning and Heating systems are significant energy consumers and critical contributors to environmental pollution. According to the 2018 Commercial Buildings Energy Consumption Survey from the U.S. Energy Information Administration, Office of Energy Statistics, Heating, Ventilation, and Air-Conditioning (HVAC) systems consume around 52% of the total commercial building energy use on average. Another report indicates that the Air-Conditioning industry is responsible for nearly 2000 million tons of carbon dioxide production, which amounts to approximately 4% of the global greenhouse gas emission annually. Previous research has targeted ways to improve the energy efficiency of HVAC systems and reduce the adverse environmental effects by improving the system performance during full and part load operating conditions via enhanced control algorithms. As is current practice, HVAC systems diagnostics are mainly executed offline by collecting data used by maintenance teams to check system performance during routine pre-scheduled maintenance activities or after an actual system failure. In the past decade, new research attention has been centered on improving the performance of HVAC systems by looking at the HVAC system as a whole and ensuring that HVAC systems perform within specification and any detected malfunction or under-performance is recognized immediately and corrected promptly.

Given the above, recent research is directed toward improving automated fault detection and diagnostics (AFDD) algorithms for HVAC systems. A robust fault detection and diagnostics strategy can reduce operating costs and improve efficiency. The typical AFDD system generally employs a library of fault rules to inform the maintenance team of needed action when there are unusual findings; the system generally can be customized to predict future system malfunctions or under-performances.

The current study aims to provide an informed and organized synopsis of the typical fault detection and diagnosis (FDD) system being researched and developed for commercial and industrial buildings. The emerged review provides insights into a few topics of concern: First, although FDD systems are fully mature in aviation, weapon systems, and other critical machinery and infrastructure, there is still a vast opportunity for the development of an open-source or less expensive FDD algorithm for HVAC systems. Second, there is a vast need for common ground to develop standards or protocols for FDD for HVAC systems. Third, machine learning may be the best approach since it would allow for a more dynamic system capable of learning from data, using the same to adapt to changing situations independently. This pathway to Artificial Intelligence (AI) may be the lynchpin to a more adaptive HVAC AFDD system.

Presenting Author: Hugh Allen-Magande Kennesaw State University

Presenting Author Biography: Hugh Allen-Magande, CEng, FASHRAE, FIMechE, is a Chartered Engineer (UK), Technical Principal (Research) at Southface Energy Institute, Inc., and a Ph.D. candidate at Kennesaw State University. He received his BEME from the City College of New York (CUNY) in 2000, where he was a recipient of The Peggy Cornell Benline Scholarship in 1998. He was awarded his MBA from Indiana Wesleyan University in 2004 and his MSEM from Rose-Hulman Institute of Technology in 2009.
Mr. Allen-Magande has more than nineteen years of experience in the thermal science field, with an emphasis on the development and deployment of high-performance HVAC and refrigeration equipment and their applications. His current research includes topics in building science, building material science, and building mechanical system investigations, applications, and technology. Mr. Allen-Magande is leading an investigation to verify and correct in‐situ system faults in residential HVAC installations.
Mr. Allen-Magande has also co-authored and published a textbook on the practical design of thermo-fluids systems and is the primary author of several operation and maintenance manuals for numerous residential and commercial HVACR equipment.
He has received several awards, including Fellow of The American Society of Heating, Refrigerating, and Air-Conditioning Engineers and Fellow of the Institution of Mechanical Engineers (UK). As a capstone, Mr. Allen-Magande was awarded two patents for his work with combination space and water heating technology and combi-system integrated controls.

Authors:

Hugh Allen-Magande Kennesaw State University
Javad Khazaii Kennesaw State University
Amin Esmaeili Kennesaw State University