METHOD OF EVALUATING AN HVAC UNIT

An HVAC system is provided in which data is obtained and reports generated. Actions can be taken with respect to the HVAC unit on the basis of the reports generated.

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Description
CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims benefit of co-pending Provisional Patent Application No. 62/586,096, filed on Nov. 14, 2017, entitled Method of Evaluating an HVAC UNIT, that application being incorporated herein, by reference, in its entirety.

BACKGROUND OF THE INVENTION Field of the Invention

An HVAC system and a method for evaluating an HVAC unit are provided in which data is collected data from a digital source, manipulates the data and calculates data points, and makes meaningful comparisons to the norm for an HVAC unit. Actions can be taken with respect to the HVAC unit based on the comparisons.

BRIEF DESCRIPTION OF THE DRAWINGS

For a fuller understanding of the nature of the present invention reference should be made to the following detailed description taken in connection with the accompanying drawings in which like reference numbers refer to like elements throughout the drawings and in which:

FIG. 1 is a simplified diagram of an HVAC system in accordance with one particular embodiment of the invention;

FIG. 2 is a chart illustrating the weighting of data for generating a health scorecard report in accordance with one embodiment of the invention;

FIG. 3 is an example of a health scorecard report generated in accordance with one particular embodiment of the present invention;

FIG. 4 is an example of another health scorecard report that can be generated in accordance with one particular embodiment of the present invention;

FIG. 5 is one example of how a health scorecard report may be displayed on a web portal interface in accordance with one particular embodiment of the invention;

FIG. 6. illustrates a portion of the code used to generate a health scorecard report in accordance with one particular embodiment of the present invention; and

FIG. 7 is a screen shot illustrating one embodiment of a SQL screen useful in connection with the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 is a simplified diagram of an HVAC system 10 in accordance with one particular embodiment of the invention, in which the health of one or more HVAC unit(s) 20 is/are determined and a report 95 is generated, using data collected from the HVAC unit 20. In use, the system 10 collects data from the HVAC unit 20. Such data can include, but is not limited to: HVAC Status; Supply Air Temperature; Return Air Temperature; DeltaT; Occupied Setpoint; Vacant Setpoint; Vacant Temperature; Total HVAC Runtime; Occupied Runtime; Vacant Runtime; Single Stage Runtime; Second Stage Runtime; Fan Runtime; Cool Runtime; Heat Runtime; Inside Humidity; Override Status; Condensate Line Backup; Outside Air Temperature; Outside Humidity; Configured Alerts; Age of Equipment; Historical Trends.

More particularly, operating data for each HVAC unit 20 is initially collected by a physical device (i.e., data source 30) inside the space and/or equipment. In one particular embodiment of the invention, the data source 30 is a thermostat associated with, and/or controlling, the respectively associated HVAC unit 20. Other data sources may be used, including other types of sensors (i.e., temperature sensor, current sensor, vibration sensor, etc.) for sensing data relating to the HVAC unit 20 and/or the environment in which it is placed. Additionally, if desired, a networking thermostat and other HVAC sensors may be used, such as is described in connection with U. S. Patent Application Publication No. 2016/0205196, incorporated herein by reference.

The data collected by the data source 30 is transmitted to a cloud computing network, such as cloud 40, through an Internet or web connection. Such a transmission can take place, for example, by an Internet connection via LAN, WAN, WiFi, Cellular GSM and/or by other known communications networks, systems and/or protocols. For example, U.S. Pat. No. 9,952,613, incorporated herein by reference, discloses one particular system and method for transmitting data from an energy management system, that can be used in connection with the present invention. In one embodiment of the invention, the data is made available to the web server(s) 50 via the “Internet of Things” (“IoT”). Additionally, in one particular embodiment of the invention, data from the thermostat(s) and/or data source(s) 30 is/are transmitted in increments of 60 seconds or less when devices are connected.

A web server 50 is connected to receive data from the data source 30 via the cloud 40 or another mechanism. In one particular embodiment, all data from the physical devices, i.e., HVAC units 20, is stored one or more databases 55 accessible from the web server 50.

An application program interface or “API” 58 is accessible by the web server 50, and executed by a processor thereof. The API 58 includes the set of rules, protocols and structure that allows others to take the data from the web server 50. In one particular embodiment of the invention, a data collector of a remote analytics system 60 (i.e., remote from the web server) provides a combination of puts and calls to the API 58 and gathers data from the web server 50. This data, once collected by the data collector 70 from the web server 50, is provided to a web server 80 of the remote analytics system 60. Web server 80 organizes the data into database 85 and stores the information that is used to create a “health scorecard” of the HVAC unit 20 from which the data came.

Algorithmic analytics 90 are performed on the data in a cloud environment and the data is manipulated to create the relevant datasets for each health scorecard report 95. The algorithms will be discussed more fully herein below. Once the data has been processed by a computer processor according to the algorithmic analytics 90, a health scorecard report 95 is populated and accessible via a web interface, from which it can be viewed downloaded, and printed.

As discussed above, in one particular embodiment of the invention, the system allows for the collection of data points, including: HVAC Status; Supply Air Temperature; Return Air Temperature; DeltaT; Occupied Setpoint; Vacant Setpoint; Vacant Temperature; Total HVAC Runtime; Occupied Runtime; Vacant Runtime; Single Stage Runtime; Second Stage Runtime; Fan Runtime; Cool Runtime; Heat Runtime;

Inside Humidity; Override Status; Condensate Line Backup; Outside Air Temperature; Outside Humidity; Configured Alerts; Age of Equipment; Historical Trends. With over 20 data points to choose from, in one particular embodiment of the invention, a health scorecard report 95 is derived from at least 7 key HVAC unit performance data points including: age; runtime; deltaT; condensate line backup; excessive fan runtime; zone not regulating; and high humidity. Four of the seven data points can be grabbed directly from the datasets the source creates, while the other three will be calculated. The three calculated values are deltaT, excessive fan runtime, and zone not regulating.

In order to generate the health scorecard report 95, each data point is assigned a weighted point value. Referring now to FIG. 2, one particular embodiment of a weighted point value system 100 will be discussed in connection with obtaining or calculating the 7 key HVAC unit performance data points listed above. In the present embodiment, each of the HVAC unit performance data points, above, has been assigned a weighted point value illustrated in FIG. 2. The choice of these specific data points, and the weights assigned for the score that they receive, comes from experience in this industry and a knowledge of how HVAC units should work.

Age of the Unit: While this may seem apparent, the age of the HVAC unit plays a large role in the overall health of the unit. Equipment is not manufactured like it used to be and, on average in our industry, HVAC components have a “useful life” of 12 years. That is not to say that every unit will break down at the 12 year mark, but we see particular, integral components have a higher likelihood of failing past 12 years; that is the reasoning for this factor accounting for 25% of the overall score (i.e., a possible 25 points out of the total 100).

Condensate Alarms: Every HVAC system plays the essential role of either removing heat from a space, or adding heat to a space. Through this heat removal process (i.e., while cooling), air is rung out of its water vapor. That condensed water leaves the HVAC unit and flows outside, normally through a pvc pipe. If the air, coil, or unit is dirty, there can be clogs of algae and other contaminants in this drainline. If this happens multiple times in a 90 day span, it is indicative of a larger possible issue. In the embodiment of FIG. 2, the number of condensate alarms in the previous 90 days contributes 5% to the overall score to be reported on the health scorecard report.

Excessive Fan Runtime: Unnecessary fan runtime refers to when the blower motor is running and circulating air when the HVAC unit itself is not heating or cooling. This excess fan runtime alert is triggered when the fan runs for at least 80% of the previous 24 hours, which causes strain on the blower and raises electric costs. In the embodiment of FIG. 2, the number of excessive fan runtimes in the previous 90 days contributes 10% to the overall score to be reported on the health scorecard report.

Runtime: When designed and implemented correctly, an HVAC system in Florida should run 60% of the time in a 365 day span (based on the typical weather in Florida). This runtime scoring can be adjusted geographically based on weather data developed for other locations. But, for the Florida example, which equates to a runtime of 5260 hours, we base our runtime score off of the percentage of 5260 hours that the unit runs. If it runs at 100% or more, it receives no points. If it runs less than that 60%, then the points go up, meaning that the HVAC unit cools the space efficiently and does not need excessive runtime. In the embodiment of FIG. 2, the runtime score (finetuned for a geographic area) contributes 25% to the overall score to be reported on the health scorecard report.

Average DeltaT: The deltaT of an HVAC system is defined as the difference between the return air temperature and supply air temperature. This is valuable information, as it is a basic identifier for how effectively an HVAC system is working as a unit should be registering a difference of 18-22 degree delta from the return air to the supply air. Taking the average of this data point over an entire year tells us how effectively the HVAC system was maintained, how efficiently is removes heat from a space, and gives insight to the normal degradation of a coil. In the embodiment of FIG. 2, the runtime score contributes 25% to the overall score to be reported on the health scorecard report.

Zone Not Regulating: This alarm is triggered when the temperature inside the space (return air) is 4 degrees or more above the cooling setpoint for more than 60 minutes. This tells us that the unit cannot keep up with the heat load and could need service or maintenance. This alert gives us more insight into the design of the unit within a space and how efficiently it cools. In the embodiment of FIG. 2, the “zone not regulating” score contributes 5% to the overall score to be reported on the health scorecard report.

High Humidity: This alert is triggered when the average humidity in the space is above 65% for more than 60 minutes. Humidity is directly correlated to the cooling of a space in that the more efficiently it cools, the more well maintained the humidity levels are. In the embodiment of FIG. 2, the “high humidity” score contributes 5% to the overall score to be reported on the health scorecard report.

FIG. 3 illustrates an exemplary health scorecard report 200, which may be the report 95 of FIG. 1, generated in accordance with one particular embodiment of the invention. Box 210 of the health scorecard report 200 details the location identifying information such as contact information and address where the HVAC system is located. Also outlined in this box is the timeline of the data that was utilized to form the score. Any span of time can be used to generate a scorecard score but it is the recommendation of our HVAC analysts that a full year be analyzed.

Box 220 is where the weighted score described above in connection with FIG. 2 is displayed. This will be a whole number with high contrast to easily draw the eye to it and have the end user get an immediate understanding of their 1-100 score.

Box 230 details the identifying information for the unit that is being evaluated and the industry averages for that type of unit. This is important information in that it attempts to educate the end user on what numbers they want to aim for in terms of average deltaT and annual runtime.

Equally as important as box 230, box 240 is the actual operational data for the unit being evaluated. Information listed here can be directly compared by the end user to the information above as a quick and easy initial understanding of their complex HVAC data.

Box 250 provides an open forum for an analyst or technician to make sensible comments and recommendations for that HVAC unit. Common topics in this section give a layman's explanation of how well the unit is operating, something positive that the unit is doing such as a good schedule, highlight any issues that the analyst sees, and a broad estimation of how much longer the unit should last.

Any HVAC unit can need a service call at one point or another but the inventors have found that units scoring over 90 in our weighted score might only need a single time that a technician has their eyes on the unit. They saw that units with lower scores require more attention as functionality of the unit wanes and components get older. Box 260 is a generic estimation of how many service calls to expect based on the weighted score to assist with budgeting of the end user.

Box 270 is a graphical representation of the total monthly runtime for the HVAC unit. It also gives another practical and easy understanding to their complex HVAC data.

Box 280 provides the customer with a name of the person reviewing the unit report 200 and/or the unit itself.

FIG. 4 illustrates another possible health scorecard report 300 formatted in accordance with another embodiment of the invention. As can be seen, the health scorecard report 300 is very similar to that discussed in connection with FIG. 3, with like reference numbers representing like elements. However, in the present embodiment, boxes 210 and 230 of FIG. 3 have been combined to form box 310 of FIG. 4.

FIG. 5 illustrates one example of how a health scorecard report 400 may be displayed on a web portal interface in accordance with one particular embodiment of the invention.

FIG. 6. is a view of a computer screen 450 a portion of the code used to generate a health scorecard report in accordance with one particular embodiment of the present invention.

FIG. 7 is a screen shot illustrating one embodiment of a SQL screen 500 useful in connection with the present invention.

The above-described algorithm is used to generate a health scorecard report which presents information to the user in a useful way and which is of value to our customer base. The present invention has the capacity to be applied to many scenarios that improve the customer's probability of making a well informed decision. The best way to demonstrate is through a story of the impact on a customer who owned 94 HVAC units on 62 properties. It is a daunting process to not only care for each of these units, but to also find the budget to replace units when they break. Using health scorecard reports generated in accordance with the present invention gives the customer a broad view of their HVAC portfolio, makes individual recommendations on when units need to be replaced based off of the data validated score. This impactful story allowed the customer to rethink everything they knew about the HVAC service industry and make decisions on the scores and not merely based on the calendar.

Additionally, it should be understood that the results of the determinations, as represented on the health scorecard reports can be used to automatically update factors in the HVAC unit. For example, data from the report can be used to provide feedback to the web server 50 of FIG. 1, that can be provided to the thermostat and used to update operating settings for the HVAC unit.

It should be understood that all algorithms described herein can be executed by computer hardware and/or software modules. All data can be acquired using hardware including sensors, thermostats and other sensing devices.

Accordingly, while a preferred embodiment of the present invention is shown and described herein, it will be understood that the invention may be embodied otherwise than as herein specifically illustrated or described, and that within the embodiments certain changes in the detail and construction, as well as the arrangement of the parts, may be made without departing from the principles of the present invention as defined by the appended claims.

Claims

1. An HVAC system, comprising:

an HVAC unit;
a data source in communication with the HVAC unit, local to the HVAC unit;
a cloud server in communication with the data source;
an analytic system remote from said cloud server, said analytic system including a data collector for collecting HVAC unit data from said cloud server and providing it to an analytics engine in order to generate a health scorecard report for the HVAC unit.

2. The system of claim 1, wherein the analytics engine provides a score based on weighted data received from the cloud server.

3. The system of claim 1, wherein an action is taken in response to the report generated.

Patent History
Publication number: 20190145646
Type: Application
Filed: Nov 14, 2018
Publication Date: May 16, 2019
Inventors: Christopher Hamilton (Fort Lauderdale, FL), Robert W. Lafferty, SR. (Fort Lauderdale, FL), Robert W. Lafferty, JR. (Fort Lauderdale, FL), Robert Pulsifer (Fort Lauderdale, FL)
Application Number: 16/190,843
Classifications
International Classification: F24F 11/38 (20060101); F24F 11/58 (20060101);