• If the coolant levels are correct, the filters are clean, and there are no other problems, the maintenance call may not have been necessary. This results in unnecessary expense and inconvenience for the homeowner.
• If system maintenance has just been performed, a leak may develop and/or a component may malfunction shortly after the maintenance call. The problem may not be noticed by the homeowner and, therefore, not corrected until the next scheduled tune-up. This could result in ever increasing utility bills for the homeowner, and it could result in permanent damage to the HVAC system.

As a result, companies are developing hardware/software products to provide a means for monitoring and maintaining optimum performance of residential HVAC units. This article provides three case studies to provide objective evidence of the value of these systems in residential HVAC installations.

INSTALLATION

For the purposes of this article, we assume a simple monitoring installation as shown in Figure 1. Three sensors are installed: (a) inlet temperature (return air), (b) outlet temperature (supply air), and (c) current sensor installed on the blower fan. While the schematic illustrates the installation for an a/c system, the same sensors are also used for heat (furnace) mode as well.

A Wi-Fi based microprocessor unit measures the outputs from the installed sensors and transmits the

data to a cloud based MySQL database every 60 seconds.  This recording frequency provides 1,440 sample points for the installed unit every 24 hours. The stored data may be downloaded from a remote location and analyzed by a back office software application.

CASE STUDY 1 — OPTIMAL PERFORMANCE

The first case study illustrates the optimal performance of an HVAC residential installation in Texas. As seen in Figure 2, the back office software program provides a delta T/AC run time percentage graph (left graph) as well as the actual inlet (yellow) and outlet (blue) temperatures (right graph). The implementation of filtering algorithms to the data set provide meaningful delta T results that minimize the effects of humidity and transient (startup) measurements from distorting the true performance of the HVAC system being monitored. In this case study, the HVAC installation is running optimally.

CASE STUDY 2 — REFRIGERANT LEAK

The second case study illustrates the value in acquiring and storing the measurement data in the time domain. The back office software utilized provides the capabilities for analyzing and providing rise time results. Rise time is defined as the amount of time (in minutes) the system requires to go from fully off to 63.2 percent of the final steady state value.  For an installed HVAC system, we desire that the a/c reach its steady state operating delta T (in this case 20°F) as well as reach the steady state operating condition in a reasonable amount of time (typically 5-10 minutes).

In this case study, we provide results from the installation where a refrigerant leak in the a/c system occurred over a period of three weeks (Figure 3).

• On 09/18/2016 the a/c unit was performing properly. The steady state delta T of the unit was 19° and the rise time was 4 minutes.
• On 09/25/2016, the a/c unit was beginning to degrade. The steady state delta T of the unit was 12.8°. At this point, the monitoring software detected that the performance of the unit had degraded. The degradation was not noticed by the homeowner.
• Finally, on 10/09/2016, the a/c unit was only able to obtain a steady state delta T of 4.2°. It was at this point the homeowner noted that the unit was not working.

The implementation of a remote HVAC monitoring and diagnostic system on this residential unit moved forward the detection of a refrigerant leak by two weeks. This event was fully recorded by the monitoring system.

CASE STUDY 3 — BAD MOTOR STARTER CAPACITOR

The last case study illustrates the implementation of the system in a residential HVAC system in Iowa. The monitoring time period shown was during the month of December, so the HVAC system was operating in heat or furnace mode. As seen in Figure 4, The output of the monitoring software provides two different graphical views of the recording data (a) inlet temperature (yellow line) to the furnace (left graph), (b) outlet temperature (blue line) of the furnace (left graph) and (c) heat rise = outlet temperature minus inlet temperature (right graph).

In this data set, the graphical results illustrate four temperature spikes that occurred over a six day time period. Further examination of the data illustrated that the furnace was turning on, but the blower fan was not. The furnace temperature would eventually set the high temperature limit switch (typically set to 155°-160°). After cooling off for several minutes, the furnace and blower would both come on successfully.

Further diagnostics of the HVAC system found that the blower fan motor starting capacitor was beginning to exhibit early indications of failure. The motor starter capacitor was replaced by the HVAC contractor on the monitored unit. This case study illustrates a situation where an issue was uncovered by the monitoring system that would have never been observed by an HVAC service technician in the field. Eventually the capacitor would have failed completely, resulting in an emergency service call to the HVAC service company by the homeowner. Instead the repair was completed during normal service hours with minimal disruption to the homeowner.

SUMMARY

The implementation of Residential HVAC Monitoring and Diagnostics systems provide a direct tool for minimizing wasted power as well as providing a means to the consumer to determine the current operating state of their installed HVAC unit.

Publication date: 6/19/2017

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