*4.5. Other Considerations*

The development and deployment of these algorithms stimulated an interesting discussion among the partners and advisors of the project about the role of the FDD and the BAS. Typically, the commercial FDD tools are developed as a software layer on top of the existing BAS. There exists a natural separation of roles in this arrangement, in which the BAS actively controls the building and the FDD tool observes its operation and provides insights and recommendations to the building manager. However, some consider FDD tools as a new generation of BAS that can take over some of its functionalities when it is necessary. At the beginning of the project, one facility manager expressed the desire to implement Guideline 36 sequences [24] on a building being controlled by an obsolete control system. To implement the sequences on that system, significant hardware upgrades and BAS programming labor would be required. The code cannot be easily reused between controllers due to the limitations of the control language, therefore this operation was not scalable and its implementation on multiple systems was hampered. As an alternative, he suggested to host the sequences in the significantly more modern FDD tool (algorithms 2.5, 2.8 and 2.9) and use the existing BAS as a simple tool to collect data and provide direct control over the lower-level hardware. This strategy was eventually implemented and was described in Section 3. Other partners disagreed, objecting that extensive real-time control of the building is outside the scope of FDD tools. Business models of the companies developing the tools may play a role in the way these new functions will be eventually incorporated in the FDD products at the end of this project.

#### **5. Conclusions and Future Work**

This paper presented nine algorithms for HVAC systems that were designed to automatically correct faults or improve operations relative to incorrectly programmed schedules, overriding manual control, sensor bias, control hunting, rogue zones and less aggressive setpoints or setpoints setback. It also showed preliminary tests confirming the e fficacy of a subset of these algorithms, as tested in a large commercial building. Finally, it discussed challenges faced during the integration of these auto-correction algorithms into three commercial FDD tools and the solutions to these challenges that were adopted by the project partners. The main challenges included: (1) developing a secure two-way communication between the FDD tool and the BAS; (2) incorporating operator approval; (3) managing the customizations necessary to the specific BAS/site installation; and (4) managing the potential conflict between the auto-correction and the BAS control actions. The suggested solutions will help future auto-correction developers address similar challenges.

With respect to automated fault auto-correction, future work will focus on more field testing of the FDD integrated correction algorithms in a cohort of existing buildings. This will include the evaluation of the technical e fficacy and the performance of each correction routine, the evaluation of the operations and maintenance benefits for each site in cohort and the characterization of challenges and best practices. A second area of future work will entail the design and execution of a techno-economic analysis to quantify the broader market opportunity to inform ongoing commercialization e fforts.

The state of today's FDD technology can be advanced through research focused on enhanced diagnostic (as opposed to detection) approaches and methods for fault prioritization. Complementary work to characterize fault prevalence based on empirical data from the field could also prove valuable in guiding future FDD technology development and implementation e fforts. There is also an overarching need to navigate issues related to data management, integration, cybersecurity, and interoperability.

**Author Contributions:** Conceptualization, J.G., Formal analysis, G.L., M.P. and Y.C.; Methodology, G.L., M.P., Y.C. and J.G.; Writing—original draft, G.L., M.P., Y.C. and J.G.; Writing Review & Editing, G.L. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research was funded by the Assistant Secretary for Energy E fficiency and Renewable Energy, Building Technologies O ffice, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

**Acknowledgments:** This work was supported by the Assistant Secretary for Energy E fficiency and Renewable Energy, Building Technologies O ffice, of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. The authors wish to acknowledge Harry Bergmann for his guidance and support of the research. We also thank the fault detection and diagnostics technology and service providers who participated in this study.

**Conflicts of Interest:** The authors declare no conflict of interest.
