Automatic control logic evaluation for secondary heating, ventilation, and air conditioning (HVAC) systems

Lead University: Carnegie Mellon University
PI: Xuesong Liu, Civil and Environmental Engineering
Co-PIs: Mario Berges, Civil and Environmental Engineering; Burcu Akinci, Civil and Environmental Engineering

This proposed research project targets at automatically detect and diagnose control logic faults in building heating, ventilation and air-conditioning (HVAC) systems. Control logic faults are caused by inconsistencies in the logic implementation with regard to the designed sequence of operation (SOO) and violations of the energy efficiency principles. Previous studies suggest that they account for more than 15% (occurrence number) of HVAC faults. There are several causes for control logic faults, such as SOO being incorrectly written by the mechanical engineer or incorrectly interpreted by the programmer, implementation mistakes and errors, inconsistent/incorrect configurations during operation and maintenance, and improper customization of control logics that are copied from other projects or templates, etc.

Current industry practice adopts two approaches to identify control logic faults: manual logic verification during system commissioning and BAS data-based automated fault detection and diagnosis (AFDD) during operation. However, manual approaches are limited in that they incur in large labor costs and are prone to human errors. Moreover, AFDD approaches identify faults that can be have multiple potential causes or can fail to detect certain types of control logic faults that require information about the control device specifications or control logic configuration.

To overcome these limitations, we propose an approach that automates the HVAC control logic verification and identifies control logic faults before system operation, utilizing software testing and model checking techniques. These techniques have been used in other domains (e.g., pacemakers and aviation) but remain untested for HVAC systems. The envisioned research outcome, then, is an approach that automatically verifies control logic programs during implementation, and alerts the control logic programmer about control logic faults so that they can correct them before the operation of HVAC systems. This will reduce energy waste and improve occupant comfort.