ASHRAE Journal - February 2020 - 22

TECHNICAL FEATURE

companies that provide these services often
FIGURE 2 The response of space conditions to changes in the heating modulation band.
charge high monthly fees for the collection
Data Alerts
Remote Change of the High
and analysis of data. However, just like the
Discharge Temperature
Change of the Heating High Discharge
Setpoint from 95°F to 100°F
manufacturers of typical household gadgets 110°F Remote
Temperature Setpoint from 90°F to 95°F
have taken advantage of IoT, some manu100°F
facturers of critical building equipment
90°F
such as DOAS have begun integrating built80°F
in IoT capabilities into their products. This
70°F
has provided DOAS manufacturers, users
60°F
4p
6p
8p
10p
16 Oct
2a
4a
6a
8a
10a
12a
and service personnel with invaluable
operating data at a much lower cost.
Average Space Temperature (Temperatures)
Discharge (Temperatures)
The process of DAQ for DOAS units must
Max Discharge (Occupied Setpoints)
be done methodically for it to provide the
Space (Occupied Setpoints)
desired capabilities. Optimal integration of
the multiple components and functionalFIGURE 3 Real-time feedback of a system's refrigeration pressures and superheat temperatures.
ities requires a comprehensive analysis of
data from each subsystem. Furthermore,
Data Alerts
data gathered from over 500 DOAS units
23°F 500 psi
has proven that effective troubleshooting
does not solely rely on sensor readings. It is
22°F 400 psi
equally important to keep track of changes
21°F 300 psi
to setpoints, which can sometimes impact
system performance negatively. Therefore,
20°F 200 psi
it is important for the DAQ process to
19°F 100 psi
include all relevant unit settings and pro9:40a 9:50a
10a 10:10a 10:20a 10:30a 10:40a 10:50a 11a 11:10a 11:20a
vide remote control capabilities for setting
Discharge Pressure (Condenser)
adjustments when necessary.
Suction Pressure (Status)
Superheat Value (Status)
Figure 2 shows the impact that a "maximum
heating discharge setpoint" of a unit can
have on its ability to maintain a target space setpoint.
algorithms that can sort the information for optimizing
Trended data acquired from the unit's sensors showed
goals. In addition, the data must be filtered and orgathat it had been operating at the maximum allowed dis- nized in a manner that simplifies the process of identifycharge temperature, which is in place to prevent undeing inefficiencies and alarms.
sired space temperature variance. However, the space
Real-time data may provide important performance
setpoint was not being reached, hence the support team information, but an integral part of the connected comdecided to progressively increase the maximum allowed missioning of DOAS units is the analysis of trends and
discharge temperature by a few degrees to improve the
aggregated data that may reveal otherwise hidden inforunit's performance without negatively impacting the
mation. For example, a high refrigeration pressure fault
space.
might initially indicate a failed condensing fan or dirty
Similarly, real-time refrigeration circuit data can be
condensing coil. However, if the system modulates conextremely useful when troubleshooting alarms and
densing airflow to maintain a floating head pressure, a
warnings remotely. Figure 3 shows pressure transducer
failed outdoor air temperature sensor can cause similar
readings over time, which can be used to assess the
effects. By cross-referencing data points over time and
potential causes for high or low refrigerant pressure
diagnosing the root cause of a fault prior to a service
alarms-typical if a unit has a leaking or clogged coil.
visit, the user saves valuable time and money.
Data Aggregation and Interpretation. Throughout
Aggregation provides a broader perspective by conthe data aggregation process, it is important to apply
densing gathered data across a particular time frame
22

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ASHRAE Journal - February 2020

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