@article{35756,
  keywords = {Fault detection and diagnostics (FDD), Smart building, Fault correction, Field testing, Control hunting, Energy management and information system},
  author = {Guanjing Lin and Marco Pritoni and Yimin Chen and Raphael Vitti and Christopher Weyandt and Jessica Granderson},
  title = {Implementation and test of an automated control hunting fault correction algorithm},
  abstract = {<p>Control hunting due to improper proportional–integral–derivative (PID) parameters in the building<br />automation system (BAS) is one of the most common faults identified in commercial buildings. It can<br />cause suboptimal performance and early failure of heating, ventilation, and air conditioning (HVAC)<br />equipment. Commercial fault detection and diagnostics (FDD) software represents one of the fastest<br />growing market segments in smart building technologies in the United States. Implementation of PID<br />retuning procedures as an auto-correction algorithm and integration into FDD software has the<br />potential to mitigate control hunting across a heterogeneous portfolio of buildings with different BAS in<br />a scalable way. This paper presents the development, implementation, and field testing of an<br />automated control hunting fault correction algorithm based on lambda tuning open-loop rules. The<br />algorithm was developed in a commercial FDD software and successfully tested among nine variable air<br />volume boxes in an office building in the United States. The paper shows the feasibility of using FDD<br />tools to automatically correct control hunting faults, discusses scalability considerations, and proposes a<br />path forward for the HVAC industry and academia to further improve this technology.</p>},
  year = {2023},
  journal = {Energy & Buildings},
  volume = {Vol.283 No..112796},
  month = {01/2023},
  doi = {https://doi.org/10.1016/j.enbuild.2023.112796},
  language = {eng},
}