US 12,222,118 B2
Systems and methods for predicting refrigerant leakage of a critically charged HVAC/Refrigeration system
Evan Aschow, Fair Oaks, CA (US); Michael May, Reno, NV (US); Joel Cesare, Santa Cruz, CA (US); and Tony Cacace, Santa Cruz, CA (US)
Assigned to GOOGLE LLC, Mountain View, CA (US)
Filed by Google LLC, Mountain View, CA (US)
Filed on Sep. 26, 2022, as Appl. No. 17/952,909.
Prior Publication US 2024/0102677 A1, Mar. 28, 2024
Int. Cl. F24F 11/38 (2018.01); F24F 11/36 (2018.01); F24F 11/63 (2018.01); F25B 45/00 (2006.01)
CPC F24F 11/38 (2018.01) [F24F 11/36 (2018.01); F24F 11/63 (2018.01); F25B 45/00 (2013.01); F25B 2345/001 (2013.01)] 7 Claims
OG exemplary drawing
 
1. A system for predicting a leak of a HVAC/Refrigeration system, the system comprising:
a cloud computing system; and
a first HVAC/Refrigeration system comprising a controller configured to at least one of communicate directly with the cloud computing system, or communicate with the cloud computing system through a user device in communication with the controller of the first HVAC/Refrigeration system; and
wherein the cloud computing system comprises processing circuitry configured to communicate with the first HVAC/Refrigeration system and a plurality of other HVAC/Refrigeration systems to:
obtain performance data and health data from the plurality of other HVAC/Refrigeration systems, wherein the performance data comprises subcooling data of the plurality of other HVAC/Refrigeration systems and at least one of superheat data or enthalpy data of the plurality of other HVAC/Refrigeration systems;
train a neural network to predict a leakage event based on the performance data and the health data, wherein the cloud computing system is configured to provide leak data to the neural network to train the neural network based on the leak data, and wherein the leak data is determined based at least in part on a comparison between a subcooling temperature of refrigerant of the other HVAC/Refrigeration systems and a threshold subcooling temperature;
obtain performance data and health data from the first HVAC/Refrigeration system;
use the neural network to predict a leak event at the first HVAC/Refrigeration system, wherein the neural network is configured to receive subcooling temperature data of the first HVAC/Refrigeration system as an input and predict the leak event of the first HVAC/Refrigeration system before or at a beginning of the leak event; and
operate a display to provide a notification to a technician or a manager regarding the predicted leak event at the first HVAC/Refrigeration system,
wherein the first HVAC/Refrigeration system and the plurality of other HVAC/Refrigeration systems are critically charged HVAC/Refrigeration systems.