Virtual calibration of a supply air temperature sensor in rooftop air conditioning units

Abstract

Supply air temperature (SAT) measurement is an important element in sequencing control and automated fault detection and diagnosis (AFDD) in HVAC systems to ensure the comfort of building occupants, decrease energy consumption, and lower maintenance cost. But in rooftop air conditioning units (RTUs) with gas-fired heating, the accuracy and reliability of manufacturer-installed supply air temperature (MSAT) sensors are notoriously difficult to attain. Experimental evaluations in this study, covering both the cooling and heating modes and using both direct measurements of a MSAT sensor and a multi-sensor measuring grid, demonstrate that direct measurements cannot obtain the true value of SAT in RTUs in the heating mode. Erratic measurement errors exist due to nonuniform temperature distribution and intensive thermal radiation in a compact chamber. An innovative indirect virtual calibration method for an MSAT sensor is proposed in this article to solve this issue. It demonstrates that a virtual calibrated MSAT sensor can provide accurate results when combined with a linear correlation for offset error that depends on heating stage and outside air damper signals. The linear correlation could be determined using the calculated temperature difference between the predicted theoretical true value of SAT and the direct MSAT measurement. This virtual calibration method is generic for all RTUs with similar construction of gas furnaces and can be implemented for long-term use. Further experimental evaluation and uncertainty analysis prove that the virtual calibration method can accurately predict the true value of SAT in RTUs within ±1.2°F (0.7°C) uncertainty. This economical technology will not only improve energy management of packaged units in sequencing control but also better facilitate real-time automated control and fault detection and diagnosis.

Acknowledgments

Diahong Yu is a PhD student and Student Member ASHRAE. Haorong Li, PhD, is assistant professor and Member ASHRAE. Yuebin Yu is PhD student. Jun Xiong, PhD, is a post doctor.