SYSTEMS AND METHODS FOR REFRIGERANT LEAKAGE DETECTION

Description

CROSS-REFERENCE TO RELATED PATENT APPLICATION

This application claims the benefit of and priority to Indian Provisional Application No. 202441073172, filed Sep. 27, 2024, the contents of which are incorporated herein by reference in their entirety.

BACKGROUND

The present disclosure relates generally to heating, ventilation, and/or air conditioning (HVAC) systems for a building.

An HVAC system is used to provide proper ventilation and maintain air quality in a confined space, for example, a commercial or household building. The HVAC system typically includes a refrigerant circuit having a compressor, a condenser, an expansion device, and an evaporator. Refrigerant is compressed in the compressor, which raises the pressure and temperature of the refrigerant. After passing through the compressor, the high pressure and high temperature refrigerant passes through the condenser, where the refrigerant rejects heat to a cooling medium. The refrigerant then passes through the expansion device, which expands the refrigerant and lowers its pressure and temperature. The refrigerant then enters the evaporator, where the refrigerant absorbs heat before reentering the compressor, thereby completing the refrigerant's cycle.

The refrigerant circuit includes various pipes or conduits connected between the compressor, the condenser, the expansion device, and the evaporator to facilitate refrigerant flow therebetween. The pipes or conduits may be susceptible to leakage. Refrigerant, if leaked, can mix with supply air and may enter a space served by the HVAC system. In some instances, refrigerants may be flammable. In these instances, it is possible for leaked refrigerant to catch fire and cause damage to components of HVAC system. Additionally, in some instances, refrigerants may be toxic in nature. Thus, leaked refrigerant interacting with occupants can potentially cause various health hazards.

SUMMARY

One implementation of the present disclosure is a system for refrigerant leak detection. The system comprises one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the processors to collect a first set of test data corresponding to one or more normal operating parameters associated with a heating, ventilation, and/or air conditioning (HVAC) system. The instructions further cause the one or more processors to collect a second set of test data corresponding to one or more abnormal operating parameters of the HVAC system. The instructions further cause the one or more processors to create a detection algorithm by defining a correlation function between the first set of test data and the second set of test data. The instructions further cause the one or more processors to receive sensor data from one or more sensors associated with the HVAC system. The instructions further cause the one or more processors to determine, using the detection algorithm, based on the sensor data, that the HVAC system has a refrigerant leakage, wherein determining that the HVAC system has the refrigerant leakage includes one or more of determining a location of the refrigerant leakage using the correlation function, or determining a root cause of the refrigerant leakage using the correlation function.

Another implementation of the present disclosure is a method for refrigerant leak detection. The method comprises receiving, by one or more processors of a system, sensor data from one or more sensors associated with a heating, ventilation, and/or air conditioning (HVAC) system. The method further comprises determining, by the one or more processors, that the HVAC system has a refrigerant leakage based on the sensor data. The method further comprises determining, by the one or more processors, a location of the refrigerant leakage based on the sensor data. The method further comprises determining, by the one or more processors, a root cause of the refrigerant leakage based on the sensor data. The method further comprises initiating by one or more processors, in response to determining that the HVAC system has the refrigerant leakage, a response action.

Another implementation of the present disclosure is a system for refrigerant leak detection. The system comprises one or more sensors configured to detect one or more parameters of a heating, ventilation, and/or air conditioning (HVAC) system. The system further comprises one or more storage devices storing instructions thereon that, when executed by one or more processors, cause the one or more processors to receive sensor data from the one or more sensors. The instructions further cause the one or more processors to determine that the HVAC system has a refrigerant leakage based on the sensor data, wherein determining that the HVAC system has the refrigerant leakage includes one or more of determining a location of the refrigerant leakage based on the sensor data or determining a root cause of the refrigerant leakage based on the sensor data. The instructions further cause the one or more processors to, responsive to determining that the HVAC system has the refrigerant leakage, initiate a response action to address the refrigerant leakage using the location or the root cause.

BRIEF DESCRIPTION OF THE DRAWINGS

Various objects, aspects, features, and advantages of the disclosure will become more apparent and better understood by referring to the detailed description taken in conjunction with the accompanying drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements.

FIG. 1 is a perspective view of a building including a heating, ventilation, or air conditioning (HVAC) system, according to an exemplary embodiment.

FIG. 2 is a block diagram of an airside system including an air handling unit (AHU) which can be used in the HVAC system of FIG. 1, according to an exemplary embodiment.

FIG. 3 is a block diagram of an AHU controller which can be used to monitor and control the AHU of FIG. 2, according to an exemplary embodiment.

FIG. 4 is a block diagram of a refrigerant loop that may be implemented in an HVAC system, according to an exemplary embodiment.

FIG. 5 is a block diagram of a system for refrigerant leak detection, according to an exemplary embodiment.

FIG. 6 is a flowchart depicting steps to create a correlation between normal and abnormal HVAC operating parameters which may be used in a detection algorithm, according to an exemplary embodiment.

FIG. 7 is a flowchart depicting steps for refrigerant leak detection using a detection algorithm, according to an exemplary embodiment.

DETAILED DESCRIPTION

Overview

Refrigerant leakage can result in a variety of negative effects. In some instances, refrigerant leakage can cause damage to components of an HVAC system. For example, because refrigerant is often flammable in nature, leaked refrigerant may catch fire, thereby causing severe damage to the components of the HVAC system. As such, fire suppression systems are generally needed to mitigate the risk of fire damage due to potential refrigerant leakages. Leaked refrigerant can also mix with supply air and ultimately reach occupants of a space serviced by the HVAC system, which may cause various health issues (e.g., breathing difficulty, headache, nose and eye irritation, nausea, vomiting). Further, many refrigerants have high Ozone Depletion Potential (ODP) and/or high Global Warming Potential (GWP). Thus, if leakage of refrigerant is not detected immediately, the leaked refrigerant can negatively impact the environment. Additionally, due to refrigerant leakage, a total amount of refrigerant flowing through the refrigerant circuit gradually reduces, thereby resulting in a lowered efficiency and potentially inadequate temperature control provided by the HVAC system.

Beneficially, the present disclosure provides a method and system for refrigerant leak detection. The method for refrigerant leakage detection may include collecting test data corresponding to both normal operating parameters and abnormal operating parameters of an HVAC system. The test data can be used to create a detection algorithm. The detection algorithm can use a correlation between test data to determine that the HVAC system has a refrigerant leakage. The detection algorithm can also determine a location of the refrigerant leakage and/or a root cause of the refrigerant leakage.

The detection algorithm of the present disclosure can be configured to estimate a probability value of a leak condition based on a predefined correlation function. The detection algorithm can receive operational data from one or more sensors on the HVAC system, which may include internet of things (IoT) sensors or sensors installed on an interior outlet of the HVAC system, to name a few examples. The detection algorithm may use the sensor data to identify a refrigerant leak. A response action may be generated to indicate the refrigerant leak. The response action can be at least one of generating an alert (e.g., a notification regarding a detected refrigerant leakage and corresponding GHG emissions), actuating one or more components of a ventilation unit, shutting down a portion of the HVAC system, prompting a technician to service or perform a maintenance action on a portion of the HVAC system, and/or prompting a technician to replace a portion of the HVAC system. An interface can also be generated to illustrate the amount of refrigerant leakage over time.

Accordingly, the systems and methods described herein for refrigerant leak detection alleviate the aforementioned drawbacks of conventional approaches. The present disclosure provides a technical solution for effectively and efficiently identifying and responding to refrigerant leakages, thereby reducing or eliminating the various negative impacts of refrigerant leakages described above.

Additionally, conventional sensors for leak detection have a variety of drawbacks. For example, conventional sensors can be expensive, difficult to install, and/or difficult to maintain. Conventional sensors can also be inefficient in detecting leaks in an HVAC system, as they may only monitor a specific portion (e.g., a particular component or area within a component) of the HVAC system. Beneficially, the systems and method described herein reduce the cost and complexity associated with conventional leak detection by utilizing sensor data captured via various IoT sensors that may already be included within the HVAC system, in combination with various established correlations, to discern information regarding the existence of likely refrigerant leakages, as well as the location and/or a root cause of the likely refrigerant leakage. Further, as described above, the methods of leak detection described herein allow for the detection of potential refrigerant leakages in a variety of locations within the HVAC system, the detection of potential locations of the refrigerant leakages, and also the determination of potential root causes of the refrigerant leakages. Accordingly, the systems and methods may provide notifications, along with indications of potential locations and root causes, thereby allowing for detected leakages to be more efficiently responded to, which further allows for the effective mitigation/reduction of associated damage caused by the refrigerant leakages, as compared to conventional leak detection systems and methods.

One or more specific embodiments will be described below. In an effort to provide a concise description of these embodiments, not all features of an actual implementation are described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers'specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.

When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features.

Building Hvac System

Referring now to FIG. 1, a perspective view of a building 10 is shown. Building 10 is served by a heating, ventilation, and/or air conditioning (HVAC) system 100. HVAC system 100 can include a plurality of HVAC devices (e.g., heaters, chillers, air handling units, pumps, fans, thermal energy storage, etc.) configured to provide heating, cooling, air conditioning, ventilation, and/or other services for building 10. For example, HVAC system 100 is shown to include a waterside system 120 and an airside system 130. Waterside system 120 may provide a heated or chilled fluid to an air handling unit of airside system 130. Airside system 130 may use the heated or chilled fluid to heat or cool an airflow provided to building 10.

HVAC system 100 is shown to include a chiller 102, a boiler 104, and a rooftop air handling unit (AHU) 106. Waterside system 120 may use boiler 104 and chiller 102 to heat or cool a working fluid (e.g., water, glycol, etc.) and may circulate the working fluid to AHU 106. In various embodiments, the HVAC devices of waterside system 120 can be located in or around building 10 (as shown in FIG. 1) or at an offsite location such as a central plant (e.g., a chiller plant, a steam plant, a heat plant, etc.) that serves one or more buildings including building 10. The working fluid can be heated in boiler 104 or cooled in chiller 102, depending on whether heating or cooling is required in building 10. Boiler 104 may add heat to the circulated fluid, for example, by burning a combustible material (e.g., natural gas) or using an electric heating element. Chiller 102 may place the circulated fluid in a heat exchange relationship with another fluid (e.g., a refrigerant) in a heat exchanger (e.g., an evaporator) to absorb heat from the circulated fluid. The working fluid from chiller 102 and/or boiler 104 can be transported to AHU 106 via piping 108.

AHU 106 may place the working fluid in a heat exchange relationship with an airflow passing through AHU 106 (e.g., via one or more stages of cooling coils and/or heating coils). The airflow can be, for example, outside air, return air from within building 10, or a combination of both. AHU 106 may transfer heat between the airflow and the working fluid to provide heating or cooling for the airflow. For example, AHU 106 can include one or more fans or blowers configured to pass the airflow over or through a heat exchanger containing the working fluid. The working fluid may then return to chiller 102 or boiler 104 via piping 110.

Airside system 130 may deliver the airflow supplied by AHU 106 (i.e., the supply airflow) to building 10 via air supply ducts 112 and may provide return air from building 10 to AHU 106 via air return ducts 114. In some embodiments, airside system 130 includes multiple variable air volume (VAV) units 116. For example, airside system 130 is shown to include a separate VAV unit 116 on each floor or zone of building 10. VAV units 116 can include dampers or other flow control elements that can be operated to control an amount of the supply airflow provided to individual zones of building 10. In other embodiments, airside system 130 delivers the supply airflow into one or more zones of building 10 (e.g., via supply ducts 112) without using intermediate VAV units 116 or other flow control elements. AHU 106 can include various sensors (e.g., temperature sensors, pressure sensors, etc.) configured to measure attributes of the supply airflow. AHU 106 may receive input from sensors located within AHU 106 and/or within the building zone and may adjust the flow rate, temperature, or other attributes of the supply airflow through AHU 106 to achieve setpoint conditions for the building zone.

Airside System

Referring now to FIG. 2, a block diagram of an airside system 200 is shown, according to some embodiments. In various embodiments, airside system 200 may supplement or replace airside system 130 in HVAC system 100 or can be implemented separate from HVAC system 100. When implemented in HVAC system 100, airside system 200 can include a subset of the HVAC devices in HVAC system 100 (e.g., AHU 106, VAV units 116, ducts 112-114, fans, dampers, etc.) and can be located in or around building 10. Airside system 200 may operate to heat or cool an airflow provided to building 10 using a heated or chilled fluid provided by waterside system 120.

In FIG. 2, airside system 200 is shown to include an economizer-type air handling unit (AHU) 202. Economizer-type AHUs vary the amount of outside air and return air used by the air handling unit for heating or cooling. For example, AHU 202 may receive return air 204 from building zone 206 via return air duct 208 and may deliver supply air 210 to building zone 206 via supply air duct 212. In some embodiments, AHU 202 is a rooftop unit located on the roof of building 10 (e.g., AHU 106 as shown in FIG. 1) or otherwise positioned to receive both return air 204 and outside air 214. AHU 202 can be configured to operate exhaust air damper 216, mixing damper 218, and outside air damper 220 to control an amount of outside air 214 and return air 204 that combine to form supply air 210. Any return air 204 that does not pass-through mixing damper 218 can be exhausted from AHU 202 through exhaust damper 216 as exhaust air 222.

Each of dampers 216-220 can be operated by an actuator. For example, exhaust air damper 216 can be operated by actuator 224, mixing damper 218 can be operated by actuator 226, and outside air damper 220 can be operated by actuator 228. Actuators 224-228 may communicate with an AHU controller 230 via a communications link 232. Actuators 224-228 may receive control signals from AHU controller 230 and may provide feedback signals to AHU controller 230. Feedback signals can include, for example, an indication of a current actuator or damper position, an amount of torque or force exerted by the actuator, diagnostic information (e.g., results of diagnostic tests performed by actuators 224-228), status information, commissioning information, configuration settings, calibration data, and/or other types of information or data that can be collected, stored, or used by actuators 224-228. AHU controller 230 can be an economizer controller configured to use one or more control algorithms (e.g., state-based algorithms, extremum seeking control (ESC) algorithms, proportional-integral (PI) control algorithms, proportional-integral-derivative (PID) control algorithms, model predictive control (MPC) algorithms, feedback control algorithms, etc.) to control actuators 224-228.

Still referring to FIG. 2, AHU 202 is shown to include a cooling coil 234, a heating coil 236, and a fan 238 positioned within supply air duct 212. Fan 238 can be configured to force supply air 210 through cooling coil 234 and/or heating coil 236 and provide supply air 210 to building zone 206. AHU controller 230 may communicate with fan 238 via communications link 240 to control a flow rate of supply air 210. In some embodiments, AHU controller 230 controls an amount of heating or cooling applied to supply air 210 by modulating a speed of fan 238.

Cooling coil 234 may receive a chilled fluid from waterside system 120 (via piping 242 and may return the chilled fluid to waterside system 120 via piping 244. Valve 246 can be positioned along piping 242 or piping 244 to control a flow rate of the chilled fluid through cooling coil 234. In some embodiments, cooling coil 234 includes multiple stages of cooling coils that can be independently activated and deactivated (e.g., by AHU controller 230, by supervisory controller 266, etc.) to modulate an amount of cooling applied to supply air 210.

Heating coil 236 may receive a heated fluid from waterside system 120 via piping 248 and may return the heated fluid to waterside system 120 via piping 250. Valve 252 can be positioned along piping 248 or piping 250 to control a flow rate of the heated fluid through heating coil 236. In some embodiments, heating coil 236 includes multiple stages of heating coils that can be independently activated and deactivated (e.g., by AHU controller 230, by supervisory controller 266, etc.) to modulate an amount of heating applied to supply air 210.

Each of valves 246 and 252 can be controlled by an actuator. For example, valve 246 can be controlled by actuator 254 and valve 252 can be controlled by actuator 256. Actuators 254-256 may communicate with AHU controller 230 via communications links 258-260. Actuators 254-256 may receive control signals from AHU controller 230 and may provide feedback signals to controller 230. In some embodiments, AHU controller 230 receives a measurement of the supply air temperature from a temperature sensor 262 positioned in supply air duct 212 (e.g., downstream of cooling coil 234 and/or heating coil 236). AHU controller 230 may also receive a measurement of the temperature of building zone 206 from a temperature sensor 264 located in building zone 206.

In some embodiments, AHU controller 230 operates valves 246 and 252 via actuators 254-256 to modulate an amount of heating or cooling provided to supply air 210 (e.g., to achieve a setpoint temperature for supply air 210 or to maintain the temperature of supply air 210 within a setpoint temperature range). The positions of valves 246 and 252 affect the amount of heating or cooling provided to supply air 210 by cooling coil 234 or heating coil 236 and may correlate with the amount of energy consumed to achieve a desired supply air temperature. AHU controller 230 may control the temperature of supply air 210 and/or building zone 206 by activating or deactivating coils 234-236, adjusting a speed of fan 238, or a combination of both.

Still referring to FIG. 2, airside system 200 is shown to include a supervisory controller 266 and a client device 268. Supervisory controller 266 can include one or more computer systems (e.g., servers, supervisory controllers, subsystem controllers, etc.) that serve as system level controllers, application or data servers, head nodes, or master controllers for airside system 200, waterside system 120, HVAC system 100, and/or other controllable systems that serve building 10. Supervisory controller 266 may communicate with multiple downstream building systems or subsystems (e.g., HVAC system 100, a security system, a lighting system, waterside system 120, etc.) via a communications link 270 according to like or disparate protocols (e.g., LON, BACnet, etc.). In various embodiments, AHU controller 230 and supervisory controller 266 can be separate (as shown in FIG. 2) or integrated. In an integrated implementation, AHU controller 230 can be a software module configured for execution by a processor of supervisory controller 266.

In some embodiments, AHU controller 230 receives information from supervisory controller 266 (e.g., commands, setpoints, operating boundaries, etc.) and provides information to supervisory controller 266 (e.g., temperature measurements, valve or actuator positions, operating statuses, diagnostics, etc.). For example, AHU controller 230 may provide supervisory controller 266 with temperature measurements from temperature sensors 262-264, equipment on/off states, equipment operating capacities, and/or any other information that can be used by supervisory controller 266 to monitor or control a variable state or condition within building zone 206.

Client device 268 can include one or more human-machine interfaces or client interfaces (e.g., graphical user interfaces, reporting interfaces, text-based computer interfaces, client-facing web services, web servers that provide pages to web clients, etc.) for controlling, viewing, or otherwise interacting with HVAC system 100, its subsystems, and/or devices. Client device 268 can be a computer workstation, a client terminal, a remote or local interface, or any other type of user interface device. Client device 268 can be a stationary terminal or a mobile device. For example, client device 268 can be a desktop computer, a computer server with a user interface, a laptop computer, a tablet, a smartphone, a PDA, or any other type of mobile or non-mobile device. Client device 268 may communicate with supervisory controller 266 and/or AHU controller 230 via communications link 272.

Ahu Controller

Referring now to FIG. 3, a block diagram illustrating AHU controller 230 in greater detail is shown, according to an example embodiment. AHU controller 230 may be configured to monitor and control various components of AHU 202 using any of a variety of control techniques (e.g., state-based control, on/off control, proportional control, proportional-integral (PI) control, proportional-integral-derivative (PID) control, extremum seeking control (ESC), model predictive control (MPC), etc.). AHU controller 230 may receive setpoints from supervisory controller 266 and measurements from sensors 318 and may provide control signals to actuators 320 and fan 238.

Sensors 318 may include any of the sensors shown in FIG. 2 or any other sensor configured to monitor any of a variety of variables used by AHU controller 230. Variables monitored by sensors 318 may include, for example, zone air temperature, zone air humidity, zone occupancy, zone CO2 levels, zone particulate matter (PM) levels, outdoor air temperature, outdoor air humidity, outdoor air CO2 levels, outdoor air PM levels, damper positions, valve positions, fan status, supply air temperature, supply air flowrate, or any other variable of interest to AHU controller 230.

Actuators 320 may include any of the actuators shown in FIG. 2 or any other actuator controllable by AHU controller 230. For example, actuators 320 may include actuator 224 configured to operate exhaust air damper 216, actuator 226 configured to operate mixing damper 218, actuator 228 configured to outside air damper 220, actuator 254 configured to operate valve 246, and actuator 256 configured to operate valve 252. Actuators 320 may receive control signals from AHU controller 230 and may provide feedback signals to AHU controller 230.

AHU controller 230 may control AHU 202 by controllably changing and outputting a control signal provided to actuators 320 and fan 238. In some embodiments, the control signals include commands for actuators 320 to set dampers 216-220 and/or valves 246 and 252 to specific positions to achieve a target value for a variable of interest (e.g., supply air temperature, supply air humidity, flow rate, etc.). In some embodiments, the control signals include commands for fan 238 to operate a specific operating speed or to achieve a specific airflow rate. The control signals may be provided to actuators 320 and fan 238 via communications interface 302. AHU 202 may use the control signals an input to adjust the positions of dampers 216-220 control the relative proportions of outside air 214 and return air 204 provided to building zone 206.

AHU controller 230 may receive various inputs via communications interface 302. Inputs received by AHU controller 230 may include setpoints from supervisory controller 266, measurements from sensors 318, a measured or observed position of dampers 216-220 or valves 246 and 252, a measured or calculated amount of power consumption, an observed fan speed, temperature, humidity, air quality, or any other variable that can be measured or calculated in or around building 10.

AHU controller 230 includes logic that adjusts the control signals to achieve a target outcome. In some operating modes, the control logic implemented by AHU controller 230 utilizes feedback of an output variable. The logic implemented by AHU controller 230 may also or alternatively vary a manipulated variable based on a received input signal (e.g., a setpoint). Such a setpoint may be received from a user control (e.g., a thermostat), a supervisory controller (e.g., supervisory controller 266), or another upstream device via a communications network (e.g., a BACnet network, a LonWorks network, a LAN, a WAN, the Internet, a cellular network, etc.).

Still referring to FIG. 3, AHU controller 230 is shown to include a communications interface 302. Communications interface 302 can be or include wired or wireless communications interfaces (e.g., jacks, antennas, transmitters, receivers, transceivers, wire terminals, etc.) for conducting data communications with various components of AHU 202 or other external systems or devices. In various embodiments, communications via communications interface 302 can be direct (e.g., local wired or wireless communications) or via a communications network (e.g., a WAN, the Internet, a cellular network, etc.). For example, communications interface 302 can include an Ethernet card and port for sending and receiving data via an Ethernet-based communications link or network. In another example, communications interface 302 can include a Wi-Fi transceiver for communicating via a wireless communications network. In another example, communications interface 302 can include a cellular or mobile phone transceiver, a power line communications interface, an Ethernet interface, or any other type of communications interface.

Still referring to FIG. 3, AHU controller 230 is shown to include a processing circuit 304 having a processor 306 and memory 308. Processor 306 may be a general purpose or specific purpose processor, an application specific integrated circuit (ASIC), one or more field programmable gate arrays (FPGAs), a group of processing components, or other suitable processing components. Processor 306 is configured to execute computer code or instructions stored in memory 308 or received from other computer readable media (e.g., CDROM, network storage, a remote server, etc.).

Memory 308 may include one or more devices (e.g., memory units, memory devices, storage devices, etc.) for storing data and/or computer code for completing and/or facilitating the various processes described in the present disclosure. Memory 308 may include random access memory (RAM), read-only memory (ROM), hard drive storage, temporary storage, non-volatile memory, flash memory, optical memory, or any other suitable memory for storing software objects and/or computer instructions. Memory 308 may include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described in the present disclosure. Memory 308 may be communicably connected to processor 306 via processing circuit 304 and may include computer code for executing (e.g., by processor 306) one or more processes described herein.

Memory 308 can include any of a variety of functional components (e.g., stored instructions or programs) that provide AHU controller 230 with the ability to monitor and control AHU 202. For example, memory 308 is shown to include a data collector 310 which operates to collect the data received via communications interface 302 (e.g., setpoints, measurements, feedback from actuators 320 and fan 238, etc.). Data collector 310 may provide the collected data to actuator controller 312 and fan controller 314 which use the collected data to generate control signals for actuators 320 and fan 238, respectively. The particular type of control methodology used by actuator controller 312 and fan controller 314 (e.g., state-based control, PI control, PID control, ESC, MPC, etc.) may vary depending on the configuration of AHU controller and can be adapted for various implementations.

Refrigerant Loop

Referring to FIG. 4, an example schematic of a portion 460 of an HVAC unit is shown. The HVAC unit can be a split air conditioning unit, a packaged air conditioning unit, or any other suitable air conditioning unit. As depicted, the HVAC unit includes a compressor 440, a condenser 462, one or more expansion devices 464 or valves, and an evaporator 466. As described above, the condenser 462 and/or the evaporator 466 may each be implemented using one or more heat exchangers. In any case, actuation of the compressor 440 generally drives circulation of refrigerant through the refrigerant conduits 454. In particular, the compressor 440 may receive refrigerant vapor from the evaporator 466, compress the refrigerant vapor, and output the compressed refrigerant vapor to the condenser 462. In some embodiments, a low GWP refrigerant is selected for use in the HVAC unit. The selection of a low GWP refrigerant may further reduce the potential negative environmental impact of refrigerant leakage. In an HVAC system where an older refrigerant was used, the HVAC system may have to be modified to be compatible with the low GWP refrigerant. For example, one or more system components of the HVAC system (e.g., a compressor, a valve, etc.) may be replaced to allow for compatibility of the HVAC system with the low GWP refrigerant.

As the refrigerant flows through the condenser 462, a first air flow 468 may be used to extract heat from refrigerant to facilitate condensing the vapor into liquid. When operating in a cooling mode, the first air flow 468 may be produced using environmental or outside air, for example, by actuating a fan. On the other hand, when operating in a heating mode, the first air flow 468 may be produced using supply air, for example, by actuating a blower assembly. Before being supplied to the evaporator 466, the refrigerant may flow through one or more expansion devices 464 to facilitate reducing pressure.

As the refrigerant flows through the evaporator 466, the refrigerant may undergo a phase change from liquid to vapor that facilitates extracting heat from a second air flow 470. When operating in a cooling mode, the second air flow 470 may be produced using supply air, for example, by actuating a blower assembly. On the other hand, when operating in a heating mode, the second air flow 470 may be produced using environmental or outside air, for example, by actuating a fan. Thereafter, the refrigerant may be circulated back to the compressor 440.

As depicted, the compressor 440 may be actuated by a motor 472 during operation. In some embodiments, the motor 472 may be a switched reluctance motor, an induction motor, an electronically commutated permanent magnet motor, and/or another suitable electromechanical motor. In other words, the motor 472 may actuate the compressor 440 when electrical power is supplied to the motor 472.

To facilitate controlling supply of electrical power to the motor 472, a variable speed drive (VSD) 474 and/or a control board 442 may be coupled to the motor 472. In particular, the variable speed drive 474 may receive alternating current (AC) electrical power having a fixed line voltage and a fixed line frequency from a power source, such as an electrical grid. Additionally, the control board 442 may control operation of the variable speed drive 474 to supply alternating current (AC) electrical power with a variable voltage and/or a variable frequency to the motor 472, for example, by controlling switching devices implemented in the variable speed drive 474. In other embodiments, the motor 472 may be powered directly from an AC power source or a direct current (DC) power source, such as a battery.

To facilitate controlling operation of the variable speed drive 474 or motor 472, as in the depicted embodiment, the control board 442 may include an analog to digital (A/D) converter 476, a microprocessor 478, non-volatile memory 480, and an interface 482. For example, to control switching in the variable speed drive 474, the microprocessor 478 may execute instructions stored in a tangible, non-transitory, computer-readable medium, such as the non-volatile memory 480, to determine control signals or commands, which may be communicated to the variable speed drive 474 via the interface 482. Additionally, the control board 442 may control switching in the variable speed drive 474 based at least in part on feedback from the motor 472 and/or other sensors, for example, as analog electrical signals, which may be converted to digital data via the analog to digital (A/D) converter 476 before processing by the microprocessor 478.

Refrigerant Leak Detection

Referring to FIG. 4, refrigerant typically passes through the compressor 440, the condenser 462, the expansion valve 464, the evaporator 466, and back to the compressor 440. Conduits 454 are provided to facilitate refrigerant flow through aforementioned components. In some instances, the conduits 454 include various joints, which may be susceptible to leakage. Further, in some instances, refrigerant may leak through the compressor 440, the condenser 462, the expansion valve 464, and/or the evaporator 466.

Referring to FIG. 5, a system 500 for detecting refrigerant leakage in an HVAC system (e.g., HVAC system 100) is shown, according to an example embodiment. The system 500 includes one or more sensors 510 provided to sense various parameters related to the HVAC system. The one or more sensors 510 can include temperature and/or pressure sensors provided to sense temperature and/or pressure of refrigerant flowing through a refrigerant circuit of an HVAC system and air flowing through the HVAC system. For example, the sensors 510 can measure temperature and/or pressure of at least one of supply air and/or return air. In some embodiments, the sensors 510 further include one or more refrigerant/gas detecting sensors for detecting leaked refrigerant (e.g., configured to detect the presence of leaked refrigerant/gas in areas or spaces) outside of the intended refrigerant circuit).

In some embodiments, the sensors 510 can be located within the HVAC system to measure aforementioned parameters. For example, a temperature sensor can be provided within the HVAC system to measure temperature of refrigerant in an evaporator coil (e.g., within the evaporator 466) of the HVAC system. Another temperature sensor can be located in a return air duct to measure temperature of return air. A temperature sensor can also be located in a supply air duct to measure temperature of supply air. Similarly, pressure sensors can also be placed in supply air duct and return air duct to measure pressure of supply air and return air, respectively. One or more sensors can also be provided in conduits carrying refrigerant from one component to another of the HVAC system. For example, with reference to FIG. 4, one or more sensors may be placed in the compressor 440, the condenser 462, the expansion valve 464, the evaporator 466, and/or conduits 454 to transmit signals indicative of sensed temperature and/or pressure data related to refrigerant.

It should be appreciated that the various sensors and sensor locations discussed above are provided as examples and are in no way meant to be limiting. In other examples, additional or fewer sensors of the same or differing types may be included in the same or other arrangements, and these variations are within the scope of the present disclosure.

Still referring to FIG. 5, the system 500 includes a controller 520 in communication with the sensors 510. The controller 520 may be a controller of an HVAC system (e.g., HVAC system 100) for which the system 500 is to be deployed. In other embodiments, the controller 520 may be independently provided to detect refrigerant leakage.

The controller 520 receives sensed data in form of signals indicative of parameters of refrigerant, supply air, and/or return air. The sensor(s) 510 may periodically establish communication with the controller 520 as per system defined rules that can be once every few seconds, once every few minutes, or once every few hours to transmit sensed data. The communication between the sensor 510 and the controller 520 can be either wired or wireless. In some instances, the sensor 510 may communicate with the controller 520 at multiple times which may be separated by a pre-determined time difference to improve accuracy. The pre-determined time difference may be a user-defined time difference provided by a user interface 530 in communication with the controller 520.

In some embodiments, the user interface 530 can include a desktop computer, a laptop computer, a tablet, a smartphone, a personal digital assistance (PDA), or any other type of mobile or non-mobile device. The controller 520 can periodically send request signals to the sensor 510 requesting sensed data. In some embodiments, the controller 520 may include a signal conditioner that is configured to convert or transform the value received from the sensor 510. For example, the signal conditioner may include one or more analogue to digital converters (e.g., similar in the A/D converter 476) to convert analogue sensed data or signals received from the sensor 510 into digital values.

The controller 520 includes a processing circuit 540 having a processor 550 and a memory 560. Processor 550 can be implemented as a general-purpose processor, an application specific integrated circuit (ASIC), one or more field programmable gate arrays (FPGAs), a group of processing components, or other suitable electronic processing components.

Memory 560 (e.g., memory, memory unit, storage device, etc.) can include one or more devices (e.g., RAM, ROM, Flash memory, hard disk storage, etc.) for storing data and/or computer code for completing or facilitating the various processes, layers and modules described herein. Memory 560 can be or include volatile memory or non-volatile memory. Memory 560 can include database components, object code components, script components, or any other type of information structure for supporting the various activities and information structures described herein. According to some embodiments, memory 560 is communicably connected to processor 550 via processing circuit 540 and includes computer code for executing (e.g., by processing circuit 540 and/or processor 550) one or more processes described herein.

In some embodiments, the controller 520 includes a database 570. Various parameter values related to refrigerant leak detection may be stored in the database 570. The parameters are typically determined on the basis of type and operating conditions of an HVAC system in which the system 500 is to be employed. In some embodiments, the predetermined parameters stored in the database 570 are editable, and a user can edit the same via the user interface 530.

Although the database 570 is shown to be within the controller 520 in FIG. 5, in some embodiments, the database 570 can be remote from the controller 520. In these instances, the controller 520 may be capable of communicatively coupling to a remote database server having the database 570. The database server may have a processor and memory for performing the database related operations discussed herein. For example, in some embodiments, the database server can include data or information regarding various refrigerant leaks and their characteristic parameter patterns, as well data or information regarding parameter patterns that are not characteristic of refrigerant leaks.

In some embodiments, the controller 520 includes a detection algorithm 580. The database 570 may store information relating to sensed data to input into the detection algorithm 580 for identifying refrigerant leaks, refrigerant leak locations, and/or refrigerant leak root causes. In some embodiments, the database 570 may include correlations between sensed parameters and refrigerant leaks, refrigerant leak locations, and/or refrigerant leak root causes. In some other embodiments, the database 570 may be provided with mathematical expressions and or rules that can be executed by the detection algorithm to identify refrigerant leaks. The detection algorithm may be in the form of a mathematical function that is executed by the controller 520. In some other embodiments, the detection algorithm may be a machine learning algorithm or an artificial intelligence algorithm, among various other types of algorithms.

In some embodiments, test data may be collected experimentally to be used to create the detection algorithm at the time of manufacturing or deploying the system 500. For example, prior to installing the system 500 in an HVAC system (e.g., HVAC system 100) or prior to manufacturing the HVAC system itself, a simulated test setup can be manufactured to collect sensed parameter values and their interrelations that are indicative of and may be used to identify refrigerant leaks, refrigerant leak locations, and/or refrigerant leak root causes. The simulated test setup can be subjected to various test conditions to collect test data that can be used to develop the detection algorithm.

For example, the simulated test setup can include simulation of normal HVAC system operating parameters (e.g., operation of the HVAC system with no refrigerant leakage) as well as simulation of various levels of abnormal HVAC system operating parameters (e.g., operation of the HVAC system with various levels of refrigerant leakage). For example, a first test may be simulated with 100% refrigerant charge; a second test may be simulated with 90% refrigerant charge, wherein 10% charge is considered to be leaked; and so on. In some embodiments, the simulation of various levels of abnormal HVAC system operating parameters may include various simulated leakage locations. These various simulated leakage locations may be at probable locations that are commonly associated with refrigerant leakages. For example, a first test may be simulated with a refrigerant leakage at a first condenser coil; a second test may be simulated with a refrigerant leakage at a second condenser coil; and so on. In some embodiments, the simulation of various root causes of abnormal HVAC system operating parameters may include various simulated refrigerant leakage root causes. For example, a first test may simulate corrosion of a condenser coil and the resulting refrigerant leakage; a second test may simulate the degradation of the HVAC system and the resulting refrigerant leakage; and so on.

In some embodiments, instead of simulations, such tests may be performed on an actual HVAC system, wherein a technician may intentionally create or otherwise respond to existing refrigerant leaks with different amounts, in different locations, and/or having different underlying root causes and record the test data corresponding to the parameters. In this case, the test data can be obtained using one or more sensors (e.g., similar to the sensors 510) deployed to sense the parameters. The test data is stored in the database 570. In some embodiments, a suitable processor, for example, the processor 550 or any other suitable processor or computing device, may be employed to extrapolate or interpolate the test data to extend the data to cover other sets of parameters that were not experimentally collected.

In some embodiments, the tests performed on the physical HVAC system 100 may include manual root cause assessments. For example, the technician can manually verify or otherwise determine the root cause of a particular leakage. In some embodiments, the tests performed on the physical HVAC system 100 may similarly include manual location assessments. For example, the technician can manually verify or otherwise determine the location of a particular leakage. Performance of the manual assessments may provide additional relevant data necessary for the detection algorithm 580 to determine a root cause and/or a location of a leak. Accordingly, the technician can provide the root cause and/or the location of a particular leak to be used when generating the correlations described herein to detect the presence, location, and/or root cause of a refrigerant leakage. In some embodiments, both simulations of test data and test data collected from the physical HVAC system are performed. Performing both of these tests allow for validation of the simulation test data. Once determined that the simulation test data is accurate, a wider range of simulations can be performed and relied upon for refrigerant leakage detection. Validation of the simulation is advantageous to reduce costs associated with testing on the actual HVAC system.

In some embodiments, the test data may be used to create classifications of various types of refrigerant leakages. For example, the test data can be sorted into classifications including leak sizes, leak locations, leak root causes, and corresponding effects on the operating parameters (e.g., refrigerant pressure, temperature, compressor power, run hours, speed, etc.). The classifications may be further used in the development of the detection algorithm 580.

In some embodiments, collecting the test data, as described above, can be performed once to develop the detection algorithm 580. In other embodiments, the sensed data from the sensors can be utilized as feedback for continuous improvement of the detection algorithm 580. For example, by periodically collecting test data to continuously improve the detection algorithm 580, changes in parameters of the HVAC system over a long operational run of the system may be efficiently captured. Capturing these changes in parameters can facilitate the detection algorithm 580 more accurately predicting refrigerant leakages when compared to collecting the test data only once.

In some embodiments, the sensors 510 of the system may be Internet of Things (IoT) sensors. For example, the IoT sensors in the system may be at least one of a temperature sensor, humidity sensor, or a pressure sensor implemented within the system 500 (e.g., the HVAC system 100). In some embodiments, the HVAC system may include preexisting IoT sensors. However, in some embodiments, additional IoT sensors can be added to the HVAC system based on testing an analysis to improve the leak detection process. The implementation of IoT sensors may allow for a higher efficiency of leak detection using the systems and methods described herein. For example, the database 580 may handle the data received by the sensors 510 in a more efficient manner when compared to other forms of sensors.

Referring now to FIG. 6, a flowchart depicting steps to build a leak detection algorithm of the system of FIG. 5, according to an exemplary embodiment. In some embodiments, at least one step and/or element of the process 600 may be performed by at least one system, device, and/or component of the system 500. For example, the processing circuit 540 may perform at least one step of the process 600. It should be understood that at least one of the various computing systems and/or devices described herein may perform at least one step and/or element of the process 600.

At step 610, a first set of test data corresponding to normal HVAC parameters (i.e., baseline performance data) is collected. For example, the first set of test data may be collected by the processing circuit 540 by running one or more simulations on an HVAC system (e.g., HVAC system 100 or another HVAC system) in which the system 500 is to be employed. The first set of test data can include various parameter values, such as, but not limited to, an evaporation coil temperature value, a return air temperature value, a supply air temperature value, etc. In this embodiment, the simulations include creating test conditions associated with having no refrigerant leakage amounts (i.e., normal HVAC parameters). The first set of data can include data for both normal and extreme operating conditions. For example, the test conditions may include both normal and severe weather conditions. As another example, the test conditions may include both normal building occupancy and extreme building occupancy (i.e., very low or very high occupancy). In some embodiments, as discussed above, the test data can be collected by performing actual tests on an HVAC system.

At step 620, a second set of test data corresponding to abnormal HVAC parameters is collected. For example, the second set of test data may be collected by the processing circuit 540 by running one or more simulations on an HVAC system (e.g., HVAC system 100 or another HVAC system) in which the system 500 is to be employed. The second set of test data can include various parameter values, such as, but not limited to, an evaporation coil temperature value, a return air temperature value, a supply air temperature value, etc. In this embodiment, the simulations may include creating various test conditions having variable refrigerant leakage amounts (e.g., various levels of abnormal HVAC parameters). In some embodiments, the various parameter values may also include parameters to provide further insight on the abnormal HVAC operation. For example, various leakage locations may be simulated in order for the system 500 to create a correlation between the HVAC parameters and a potential refrigerant leakage location. For example, these simulations may be done at probable leakage points. In another example, various root causes of refrigerant leakage may be simulated in order for the system 500 to create a correlation between the HVAC parameters and a potential root cause of the refrigerant leakage. The various root causes may include causes including, but not limited to, poor installation of one or more components of the HVAC system, corrosion of one or more components of the HVAC system, one or more components of the HVAC system being defective, or degradation due to wear of one or more components of the HVAC system. In some instances, the various root causes may be identified based on historical data. For example, the database 570 may include historical data pertaining to root causes of previous leakages in the HVAC system. In some embodiments, as discussed above, the test data can be collected by performing actual tests on an HVAC system.

At step 630, a correlation between the first set of test data and the second set of test data is created. For example, a detection algorithm 580 that utilizes a correlation between the normal HVAC operating parameters collected at step 610 and the abnormal HVAC operating parameters collected at step 620 may be built at this step by the processing circuit 540. In some embodiments, the detection algorithm 580 may be a mathematical function that is a correlation of leak rate as a function of major operating parameters. In some embodiments, based on the correlation, the detection algorithm 580 may also estimate a leak probability value. For example, the leak probability value may indicate the severity of the abnormality. In some embodiments, the detection algorithm 580 may alternatively be implemented as a machine learning model or another artificial intelligence model. In some such implementations, the detection algorithm 580 may be using generative artificial intelligence models, such as generative adversarial networks, transformer models (e.g., generative pretrained transformers), and/or other types of generative artificial intelligence models.

In some embodiments, the correlation created at step 630 may be used to identify a location of the refrigerant leakage. For example, based on the correlation, the detection algorithm 580 may determine the location of the refrigerant leakage. In some embodiments, the correlation may include data patterns relating to various sensors located at various locations of the system 500 (e.g., the HVAC system 100). The correlation may also include data patterns relating to various sensor data values collected as a result of simulations of leakages at various system locations. Using the data patterns collected from the test data, the detection algorithm 580 may determine the location of the refrigerant leakage.

In some embodiments, the correlation created at step 630 may be used to identify a root cause of the refrigerant leakage. For example, based on the correlation, the detection algorithm 580 may determine the root cause of the refrigerant leakage. In some embodiments, the correlation may include data patterns relating to various sensor data values collected as a result of simulations of leakages caused by different root causes. Using the data patterns collected from the test data, the detection algorithm 580 may determine the root cause of the refrigerant leakage.

Referring now to FIG. 7, a flow diagram depicting a method 700 for refrigerant leak estimation using the leak detection algorithm 580, according to an exemplary embodiment. In some embodiments, at least one step and/or element of the process 700 may be performed by at least one system, device, and/or component of the system 500. For example, the processing circuit 540 may perform at least one step of the process 700. It should be understood that at least one of the various computing systems and/or devices described herein may perform at least one step and/or element of the process 700.

At step 710, the controller receives sensed data from the sensors. In some instances, the sensed data may be stored in the database 570 and the controller 520 may condition sensed data before storing the same in the database 570. For example, the controller 520 may convert signals received from the sensors 510 into digital values and may store the digital values in the database 570 with a timestamp.

At step 720, the detection algorithm 580 receives the sensed data and determines whether the sensed data is indicative of a refrigerant leakage. For example, the controller 520 may transmit the sensed data as an input to the detection algorithm 580 where the detection algorithm 580 may perform various operations on the sensed data based on the correlation developed in process 600. At this step, the detection algorithm 580 determines whether the sensed data from the sensors 510 is indicative of a refrigerant leakage. For example, the leak probability value for the sensed data may be determined based on the correlation developed in process 600. If the detection algorithm 580 determines that the sensed data is not indicative of a refrigerant leakage, the controller 520 continues to receive sensed data from the sensors 510, at step 710, and feed the sensed data to the detection algorithm 580 at step 720.

Upon determination of a refrigerant leakage, at step 730, the detection algorithm 580 determines a location of the refrigerant leakage. For example, the detection algorithm 580 may determine the location of the refrigerant leakage based on the correlation developed in process 600. The detection algorithm 580 may be able to detect various potential locations, such as locations within various coils, valves, compressors, or tubes of the HVAC system. In some embodiments, the detection algorithm 580 determines an actual location of the refrigerant leakage. In this case, the detection algorithm 580 can successfully determine the refrigerant leakage location using the correlation. In some embodiments, the detection algorithm 580 determines a predicted location of the refrigerant leakage based on a likelihood (e.g., above a threshold likelihood) of the refrigerant leakage being in a particular location based on the correlation. In this case, the controller 520 may update the interface 530 to display instructions to verify the location of the refrigerant leakage. For example, the instructions displayed on the interface 530 may provide a list of actions for a technician to perform onsite to verify the location of the refrigerant leakage.

Upon determination of a refrigerant leakage, at step 740, the detection algorithm 580 also determines a root cause of the refrigerant leakage. For example, the detection algorithm 580 may determine the root cause of the refrigerant leakage based on the correlation developed in process 600. In some embodiments, the detection algorithm 580 determines an actual root cause of the refrigerant leakage. In this case, the detection algorithm 580 can successfully determine the refrigerant leakage root cause using the correlation. In some embodiments, the detection algorithm 580 determines a predicted root cause of the refrigerant leakage based on a likelihood (e.g., above a threshold likelihood) of the refrigerant leakage being caused by a particular underlying issue based on the correlation. In this case, the controller 520 may update the interface 530 to display instructions to verify the refrigerant leak root cause. For example, the instructions displayed on the interface 530 may provide a list of actions for a technician to perform onsite to verify the root cause of the refrigerant leakage.

At step 750, the controller 520 initiates one or more response actions to address the refrigerant leakage. For example, upon determining that refrigerant is leaking/leaked through the HVAC system in which the system 500 is employed (e.g., the HVAC system 100) as well as the location and the root cause of the leakage, the controller 520 automatically initiates one or more response actions. For example, in some embodiments, the controller 520 may transmit an alarm. The alarm may be at least one of a notification (e.g., a notification regarding a detected refrigerant leakage and corresponding GHG emissions), a visual alarm, an audio alarm, or any combination thereof. In some embodiments, the controller 520 may transmit alarm signals on the user interface 530. The user interface 530 can be a part of the HVAC system in which the system 500 is deployed (e.g., the HVAC system 100) or can be an independent user interface provided with users. For example, the user interface 530 may be included on a mobile device associated with a user with permissions for operations relating to the system 500. In some embodiments, the controller 520 may transmit different alarms to represent different locations of the refrigerant leakage. For example, if the leakage is located within an evaporator coil of the HVAC system, the controller 520 may transmit a notification to the user interface which explicitly states the evaporator coil that is causing the leakage. In some embodiments, the controller 520 may transmit different alarms to represent different root causes of the refrigerant leakage. For example, if the refrigerant leakage was caused by corrosion of a condenser coil, the controller 520 may transmit a notification to the user interface which explicitly states that there is a refrigerant leakage present caused by corrosion of the condenser coil. In some embodiments, the alarm may provide information indicative of both the location and the root cause of the leakage.

In some embodiments, the response actions may include the controller 520 modifying operation of the HVAC system and or various other systems upon detection of the refrigerant leakage. For example, modifying operation of the HVAC system may include generation of the alarm (e.g., if the alarm is part of the HVAC system itself). In some instances, the controller 520 may modify the operation of the HVAC system via one or more actuators 590 (e.g., similar to the actuators 224, the actuators 226, the actuators 228, the actuators 254, the actuators 256, the actuators 320, and/or any other suitable actuator type). Further, the controller 520 may operate a ventilation system that is a part of, associated with, or near the HVAC system to blow off air contaminated with refrigerant. The controller 520 may actuate blowers of the ventilation system for removing refrigerant-contaminated air. In some embodiments, the controller 520 may shut down the HVAC system to prevent further leakage of the refrigerant. For example, the controller 520 may generate a control signal to shut down a compressor of the HVAC system. In some embodiments, modification of the operation of the HVAC system may be directly related to at least one of the location or root cause of the leakage. For example, the compressor that the controller 520 shuts down may be the location of the leakage, therefore the shutting down of said compressor would resolve the leakage.

In some embodiments, the response actions may include the controller 520 transmitting one or more prompts to service technicians. For example, the controller 520 may transmit a prompt to a device associated with a technician (e.g., the client device 268) prompting the technician to service or perform a maintenance action on a portion of the HVAC system. In some instances, the controller 520 may transmit a prompt to a device associated with a technician (e.g., the client device 268) prompting the technician to replace a portion of the HVAC system.

In some embodiments, the performance of the detection algorithm 580 may be confirmed using actual onsite system performance. For example, the leakage estimation determined by the detection algorithm 580 may cause the processor to generate a notification with information pertaining to the refrigerant leakage. The notification may provide a set of instructions for a user to perform maintenance on the HVAC system onsite. In this example, the findings of the detection algorithm 580 can be compared to the findings seen onsite. In the event that there are any discrepancies between the findings of the detection algorithm 580 and the findings seen onsite, the detection algorithm 580 may be updated with relevant new findings in order to resolve any discrepancies.

In some embodiments, the sensor data may be stored over time to estimate a cumulative loss of refrigerant over time from the equipment. For example, the controller 520 may store the sensed data received at step 710 in the database 570. In some embodiments, the detection algorithm 580 may be employed to estimate a cumulative loss of refrigerant over time from the equipment based on the collection of the sensed data. In some embodiments, the cumulative loss over time may be used to create a graph. For example, the interface may display a graph which visually displays the cumulative loss of refrigerant over a selected period of time. In some embodiments, the detection algorithm 580 may also deduce a cumulative greenhouse gas (GHG) emission footprint based on the sensed data. The GHG footprint may be used to assess the environmental impact of the system 500 (e.g., the HVAC system 100). In some embodiments, the cumulative loss of refrigerant over time can be used to generate corrective measures to improve the loss of refrigerant over time. For example, the interface may display one or more corrective measure suggestions, such as repair or replacement of a component of the system 500.

In some embodiments, the response action initiated by the controller at step 750 may include notifications relating to the determined GHG footprint. For example, the controller 520 may transmit a notification to the interface 530 relating to the GHG footprint of the HVAC system. In some embodiments, the interface 530 may be a user interface on a device that employs a mobile app, SMS, or online monitoring portal. The user interface may also provide other relevant factors relating to GHG emissions, such as information on proper usage of the equipment, and the impact of refrigerant leaks on GHG emissions and thereby on the environment. The user interface may also provide a notification for timely servicing and replacement of a component of the system 500.

In one exemplary embodiment, the processes and methods described herein may implement a digital twin system to determine refrigerant leakage of an HVAC system. For example, the output of the detection algorithm 580 can be integrated with a system of digital twins. Additional features and advantages of the implementation of a digital twin system to determine refrigerant leakage are described in detail in U.S. patent application Ser. No. 18/895,144 filed Sep. 24, 2024, the entire disclosure of which is incorporated by reference herein.

Configuration of Exemplary Embodiments

The construction and arrangement of the systems and methods as shown in the various exemplary embodiments are illustrative only. Although only a few embodiments have been described in detail in this disclosure, many modifications are possible (e.g., variations in sizes, dimensions, structures, shapes and proportions of the various elements, values of parameters, mounting arrangements, use of materials, colors, orientations, etc.). For example, the position of elements can be reversed or otherwise varied, and the nature or number of discrete elements or positions can be altered or varied. Accordingly, all such modifications are intended to be included within the scope of the present disclosure. The order or sequence of any process or method steps can be varied or re-sequenced according to alternative embodiments. Other substitutions, modifications, changes, and omissions can be made in the design, operating conditions and arrangement of the exemplary embodiments without departing from the scope of the present disclosure.

The present disclosure contemplates methods, systems and program products on any machine-readable media for accomplishing various operations. The embodiments of the present disclosure can be implemented using existing computer processors, or by a special purpose computer processor for an appropriate system, incorporated for this or another purpose, or by a hardwired system. Embodiments within the scope of the present disclosure include program products comprising machine-readable media for carrying or having machine-executable instructions or data structures stored thereon. Such machine-readable media can be any available media that can be accessed by a general purpose or special purpose computer or other machine with a processor. By way of example, such machine-readable media can comprise RAM, ROM, EPROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code in the form of machine-executable instructions or data structures and which can be accessed by a general purpose or special purpose computer or other machine with a processor. Combinations of the above are also included within the scope of machine-readable media. Machine-executable instructions include, for example, instructions and data which cause a general-purpose computer, special purpose computer, or special purpose processing machines to perform a certain function or group of functions.

Although the figures show a specific order of method steps, the order of the steps may differ from what is depicted. Also, two or more steps can be performed concurrently or with partial concurrence. Such variation will depend on the software and hardware systems chosen and on designer choice. All such variations are within the scope of the disclosure. Likewise, software implementations could be accomplished with standard programming techniques with rule-based logic and other logic to accomplish the various connection steps, processing steps, comparison steps and decision steps.