Systems and methods for Refrigerant unit life cycle management

A method for tracking refrigerant of a HVAC/Refrigeration system, the method comprising:

• obtaining a signal from a sensor of a service tool, the service tool configured to removably couple with a service port of the HVAC/Refrigeration system to define a fluid flow path between a reservoir of the service tool and an inner volume of a tubular member of the HVAC/Refrigeration system, wherein the service tool is configured to add refrigerant to the HVAC/Refrigeration system or remove refrigerant from the HVAC/Refrigeration system;
• determining, based on the signal, at least one of an amount of refrigerant added to the HVAC/Refrigeration system or an amount of refrigerant removed from the HVAC/Refrigeration system;
• determining, based on at least one of the amount of refrigerant added to the HVAC/Refrigeration system or the amount of refrigerant removed from the HVAC/Refrigeration system, a current refrigerant level in the HVAC/Refrigeration system;
• operating a display to provide at least one of the amount of refrigerant added, the amount or refrigerant removed, or the current refrigerant level of the HVAC/Refrigeration system to a user;
• obtaining subcooling temperature data of the HVAC/Refrigeration system;
• predicting, using machine learning and a root cause database, a leakage event, a predicted time of the leakage event, and a root cause of the leakage event, wherein the leakage event is a reduction of the refrigerant in the HVAC/Refrigeration system, based on (i) the subcooling temperature data and (ii) mechanical health data of at least a compressor of the HVAC/Refrigeration system, the root cause database comprising a plurality of entries of leakage events and subcooling temperature data leading up to the leakage event;
• operating the display to notify the user regarding the predicted leakage event and the root cause;
• and
• automatically initiating an activity to perform maintenance on the HVAC/Refrigeration system by the predicted time of the leakage event.

A system for tracking refrigerant and status of a plurality of refrigerated display cases, a plurality of HVAC/Refrigeration units, a plurality of rooftop units, or a plurality of heat pump units, the system comprising:

• a plurality of refrigerated units, each refrigerated unit comprising a HVAC/Refrigeration system configured to cool an inner volume of the refrigerated unit;
• a user device configured to establish communication with a cloud computing system, the user device configured to communicate with processing circuitry of a service tool to provide data from the service tool regarding an amount of refrigerant added or removed from any of the plurality of refrigerated units;
• wherein the cloud computing system is configured to:
• obtain a unique identifier indicating which of the plurality of refrigerated units the data from the user device is associated with;
• obtain the data from the user device regarding the amount of refrigerant added or removed from a particular one of the plurality of refrigerated units;
• store the data regarding the amount of refrigerant added or removed from the particular one of the plurality of refrigerated units in a database associated with the unique identifier, the database comprising the data regarding the amount of refrigerant added or removed from the plurality of refrigerated units for each time a servicing operation is performed at the plurality of refrigerated units;
• operate a display to provide an inventory tracking report illustrating an amount of refrigerant present in the plurality of refrigerated units and an amount of refrigerant consumed over a lifetime of at least one of the plurality of refrigerated units based on the database;
• obtain subcooling temperature data of one of the HVAC/Refrigeration systems;
• predict, using machine learning and a root cause database, a leakage event, a predicted time of the leakage event, and a root cause of the leakage event, wherein the leakage event is a reduction of the refrigerant in the HVAC/Refrigeration system, based on (i) the subcooling temperature data and (ii) mechanical health data of at least a compressor of the HVAC/Refrigeration system, using machine learning and a root cause database, the root cause database comprising a plurality of entries of leakage events and subcooling temperature data leading up to the leakage event;
• operate the display to notify the user regarding the predicted leakage event and the root cause;
• and
• automatically initiate an activity to perform maintenance on the HVAC/Refrigeration system by the predicted time of the leakage event.