A method for estimating refrigerant charge for an HVACR system is provided. The method includes obtaining one or more system parameters during operation. The one or more system parameters include at least one of compressor suction superheat, system mass flow, expansion device mass flow or opening degree, compressor suction saturated temperature, and compressor discharge saturated temperature. The method also includes conducting a regression analysis on the one or more system parameters to determine one or more predictive parameters for estimating the refrigerant charge. The method further includes determining a predictive model based on regression analysis. The predictive model establishes a relationship between the refrigerant charge and the one or more predictive parameters. Also the method includes estimating the refrigerant charge based on the predictive model.

In various embodiments, a process for providing anomaly detection for refrigeration systems includes receiving telemetry data of one or more refrigeration systems, including measured temperature values and setpoint temperature values; processing the telemetry data to determine machine learning input data based at least in part on at least a portion of the measured temperature values and at least a portion of the setpoint temperature values; and using one or more hardware processors to apply the machine learning input data to a trained anomaly detection machine learning model to determine periodic anomaly metrics. The process provides an automatically determined indication based at least in part on at least a portion of the periodic anomaly metrics.

Methods and systems are described for anomaly detection in refrigeration systems. A process for providing anomaly detection for refrigeration systems includes receiving telemetry data of one or more refrigeration systems, including measured temperature values and setpoint temperature values; processing the telemetry data to determine machine learning input data based at least in part on at least a portion of the measured temperature values and at least a portion of the setpoint temperature values; and using one or more hardware processors to apply the machine learning input data to a trained anomaly detection machine learning model to determine periodic anomaly metrics. The process provides an automatically determined indication based at least in part on at least a portion of the periodic anomaly metrics.

An apparatus includes a high side heat exchanger, a heat exchanger, a flash tank, a first expansion valve, a second expansion valve, a load, a first compressor, and a second compressor. During a first mode of operation, the second expansion valve directs refrigerant from the flash tank to the load. The refrigerant from the load bypasses the first compressor. The heat exchanger transfers heat from the refrigerant from the high side heat exchanger to the refrigerant from the load. The second compressor compresses the refrigerant from the heat exchanger. During a second mode of operation, the first expansion valve directs refrigerant from the flash tank to the load. The first compressor compresses the refrigerant from the load and the second compressor compresses the refrigerant from the first compressor before the refrigerant from the first compressor reaches the high side heat exchanger.

A refrigerant metering system/method incorporating a manual expansion valve (MEV), condenser isolation valve (CIV), flow isolation valve (FIV), and evaporator isolation valve (EIV) is disclosed. The MEV is configured to replace a conventional automated expansion valve (AEV) that controls a refrigerant flow valve (RFV) that is positioned in a heating, ventilation, and air conditioning (HVAC) system between a refrigerant condenser coil (RCC) and a refrigerant evaporator coil (REC) and permits manual metering of refrigerant by the RFV from the RCC to the REC and also allows complete shutoff of refrigerant flow by the RFV from the RCC to the REC. The MEV allows rapid HVAC repair and restoration of service where a replacement AEV is not readily available. The CIV/FIV/EIV are positioned in the refrigerant flow lines to permit the AEV and/or REC to be isolated from HVAC refrigerant flow for repairs to the AEV and/or REC.

A compressor including a housing, a shaft configured to be rotated relative to the housing to compress a refrigerant, a motor configured to drive the shaft, a lubrication system configured to supply lubricant to the compressor, and a bearing configured to support the shaft. The shaft includes a wear-resistant sleeve-like treatment on at least a portion of an outer surface of the shaft adjacent the bearing. The lubricant is POE oil or a lubricant blend composition that includes two or more lubricants, the two or more lubricants including a first lubricant and a second lubricant.

A refrigerant metering system/method incorporating a manual expansion valve (MEV), condenser isolation valve (CIV), flow isolation valve (FIV), and evaporator isolation valve (EIV) is disclosed. The MEV is configured to replace a conventional automated expansion valve (AEV) that controls a refrigerant flow valve (RFV) that is positioned in a heating, ventilation, and air conditioning (HVAC) system between a refrigerant condenser coil (RCC) and a refrigerant evaporator coil (REC) and permits manual metering of refrigerant by the RFV from the RCC to the REC and also allows complete shutoff of refrigerant flow by the RFV from the RCC to the REC. The MEV allows rapid HVAC repair and restoration of service where a replacement AEV is not readily available. The CIV/FIV/EIV are positioned in the refrigerant flow lines to permit the AEV and/or REC to be isolated from HVAC refrigerant flow for repairs to the AEV and/or REC.

A refrigerant metering system/method incorporating a manual expansion valve (MEV), condenser isolation valve (CIV), flow isolation valve (FIV), and evaporator isolation valve (EIV) is disclosed. The MEV is configured to replace a conventional automated expansion valve (AEV) that controls a refrigerant flow valve (RFV) that is positioned in a heating, ventilation, and air conditioning (HVAC) system between a refrigerant condenser coil (RCC) and a refrigerant evaporator coil (REC) and permits manual metering of refrigerant by the RFV from the RCC to the REC and also allows complete shutoff of refrigerant flow by the RFV from the RCC to the REC. The MEV allows rapid HVAC repair and restoration of service where a replacement AEV is not readily available. The CIV/FIV/EIV are positioned in the refrigerant flow lines to permit the AEV and/or REC to be isolated from HVAC refrigerant flow for repairs to the AEV and/or REC.

A refrigerant metering system/method incorporating a manual expansion valve (MEV), condenser isolation valve (CIV), flow isolation valve (FIV), and evaporator isolation valve (EIV) is disclosed. The MEV is configured to replace a conventional automated expansion valve (AEV) that controls a refrigerant flow valve (RFV) that is positioned in a heating, ventilation, and air conditioning (HVAC) system between a refrigerant condenser coil (RCC) and a refrigerant evaporator coil (REC) and permits manual metering of refrigerant by the RFV from the RCC to the REC and also allows complete shutoff of refrigerant flow by the RFV from the RCC to the REC. The MEV allows rapid HVAC repair and restoration of service where a replacement AEV is not readily available. The CIV/FIV/EIV are positioned in the refrigerant flow lines to permit the AEV and/or REC to be isolated from HVAC refrigerant flow for repairs to the AEV and/or REC.

A method for estimating refrigerant charge for an HVACR system is provided. The method includes obtaining one or more system parameters during operation. The one or more system parameters include at least one of compressor suction superheat, system mass flow, expansion device mass flow or opening degree, compressor suction saturated temperature, and compressor discharge saturated temperature. The method also includes conducting a regression analysis on the one or more system parameters to determine one or more predictive parameters for estimating the refrigerant charge. The method further includes determining a predictive model based on regression analysis. The predictive model establishes a relationship between the refrigerant charge and the one or more predictive parameters. Also the method includes estimating the refrigerant charge based on the predictive model.