Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units

Fernandez, Nicholas; Brambley,; Katipamula, S.

doi:10.2172/973449

Cited by 9 publications

(19 citation statements)

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“…The PNNL team has developed algorithms for automatically correcting selected soft faults in airhandler dampers and sensors (Fernandez et al 2009). These algorithms have been coded in software and tested on an air-handling unit under laboratory conditions in the fall of 2009.…”

Section: Pnnl-19074mentioning

confidence: 99%

“…The self-correction algorithms developed in this project are described in detail in the companion document Self-Correcting HVAC Controls: Algorithms for Sensors and Dampers in Air-Handling Units (Fernandez et al 2009). The algorithms address faults for temperature sensors, humidity sensors, and dampers in air handling units, including their use for economizing.…”

Section: Algorithms Developedmentioning

confidence: 99%

“…In the passive detection column, the type of passive test that was responsible for the detection of the fault (when applicable) is displayed. Two passive tests are used to detect a temperature sensor fault (see Fernandez et al 2009). The "Temperature Sensor Passive Diagnostic Test" (Fernandez et al 2009, Figure 5; see Appendix), abbreviated in the "Passive Detection" column of Table 2 as "Temp," checks whether the mixed-air temperature is within the bounds of the return-air and the outdoor-air temperatures, because a failure to be within these bounds is physically impossible and indicates a sensor error.…”

Section: Temperature Sensor Bias Testsmentioning

confidence: 99%

“…Two passive tests are used to detect a temperature sensor fault (see Fernandez et al 2009). The "Temperature Sensor Passive Diagnostic Test" (Fernandez et al 2009, Figure 5; see Appendix), abbreviated in the "Passive Detection" column of Table 2 as "Temp," checks whether the mixed-air temperature is within the bounds of the return-air and the outdoor-air temperatures, because a failure to be within these bounds is physically impossible and indicates a sensor error. The second test, the "Minimum Occupied Position Passive Test" (Fernandez et al 2009, Figure 6; see Appendix), checks whether the observed OAF at the minimum occupied position is close enough to the expected OAF at the minimum occupied position, based on response curve for the outdoor-air damper (like that shown in Figure 7) and accounting for the temperature sensor tolerances.…”

Section: Temperature Sensor Bias Testsmentioning

confidence: 99%

“…The red lines represent the limits for detection of a fault for detection of a fault. These limits are based on the tolerances set for the temperature sensors, which are propagated through the OAF calculation (see Fernandez et al 2009, Section 2.5), and thus are functions of the difference between the outdoor-air and return-air temperatures. The virtual OAF fluctuates during the test but always remains within the bounds for its expected value.…”

Section: Temperature Sensor Bias Testsmentioning

confidence: 99%

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Self-Correcting HVAC Controls Project Final Report

Fernandez¹,

Brambley²,

Katipamula³

et al. 2010

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The objective of the project was to develop and laboratory test algorithms that implement selfcorrection capabilities for sensors, economizer dampers, and damper actuators in building airhandling systems. Satisfaction of this objective led to 1) algorithms ready for implementation in or connected to building and equipment control systems for field demonstration and commercial application and 2) underlying methods that may be transferable to creating selfcorrecting capabilities for other heating, ventilating, and air-conditioning (HVAC) system components. Full-scale commercial deployment of this technology will capture significant energy savings by automatically eliminating many of the faults that degrade the efficiency of HVAC systems, thus maintaining energy efficiency well above the efficiency at which these systems routinely operate. Furthermore, to the extent that HVAC electricity use and system peaking are coincident (e.g., in the summer), peak demand will also be reduced by deployment of this technology.Algorithms were developed for detecting, isolating, characterizing and correcting the following specific faults: biases in temperature and relative-humidity sensors in outdoor-, return-and mixed-air streams,  an incorrectly set signal to position the outdoor-air damper of an air handler to meet the minimum ventilation requirements of the building while it is occupied,  hunting (continuously oscillating) dampers, and  controllers left in a state of manual control override that should be in an automatic control mode.Laboratory tests for biased temperature and humidity sensors and incorrectly set values of the minimum occupied outdoor-air damper position signal showed that automatic self-correction of these faults can be successfully performed; however, under some conditions passive detection of the presence of a fault may not be possible, and the fault isolation process may reach an incorrect conclusion under some circumstances. The primary cause of incorrect conclusions in fault isolation were found to be caused by dampers leaking when completely closed. This problem can be addressed by modifying the algorithms to automatically account for imperfections in damper sealing, which is recommended.Other recommendations for future work include:iv  other enhancements to the existing algorithms,  additional laboratory testing to more completely characterize algorithm performance under a wide range of conditions and to better quantify the limits of fault detectability, isolation and correction,  laboratory test additional algorithm capabilities not tested in the present project,  development of self-correcting control algorithms for discharge-air temperature, humidity and static pressure control,  develop self correcting control algorithms for additional HVAC equipment, such as air distribution, chilled-and hot-water distribution, cooling towers, etc.,  study to quantify the benefits of deployment and use of self-correcting HVAC control technology for various systems,  development of models for commercial ...

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Section: Pnnl-19074mentioning

confidence: 99%

Section: Algorithms Developedmentioning

confidence: 99%