Carrier Corporation

Slaven Stricevic

Alan Matthew Finn

Pengju Kang

Mohsen Farzad

Payman Sadegh

A method and system for detecting and predicting air filter condition for an air handling system operates by determining a system resistance to air flow. The system resistance is utilized to determine a detection statistic indicative of current filter condition and to predict remaining life of the air filter. The system resistance is determined using models that approximate the expected operation of the air handling system. The approximation is then compared to actual values to obtain a difference. Once the difference between the approximated value exceeds a threshold value, an alarm is initiated that is indicative of system resistance. The remaining air filter life is then determined by using historically gathered data, or by using a known degradation rate of the air filter. Once the remaining life of the air filter is estimated, replacement can be scheduled that would coincide with other maintenance.

Technique for detecting and predicting air filter condition

The temperature of the air exiting an evaporator and the relative humidity of the air entering and exiting the evaporator can be calculated by using existing sensors in a vapor compression system. The temperature of the air exiting the evaporator is calculated by using the detected temperature of the air entering the evaporator, the saturation temperature of the air, and a bypass factor. The relative humidity of the air entering and exiting the evaporator are then estimated using a psychrometric chart. By using the existing sensors to determine the temperature of the air exiting the evaporator and the relative humidity of the air entering and exiting the evaporator, the load requirement of the vapor compression system can be calculated without employing additional sensors. The system capacity of the vapor compression system can be matched to the load requirement to allow the effective use of electric power.

Method for estimating inlet and outlet air conditions of an HVAC system

A method of diagnosing sensor faults for a heating, ventilation and air conditioning system includes the steps of creating a component model for a specific component within the system. The component model is created through the use of commonly available manufacturing data. Data within the system is input into the component model and compared to calculated and predicted values that are also calculated using the identical component models. Differences between the calculated and actual values is determined and compared to a threshold difference value. If the difference exceeds the threshold value, then a fault is detected. The specific type of sensor fault is determined using probability distribution analysis. Each type of sensor fault produces a different type of statistical deviation from normal distribution. By recognizing these patterns of deviations from the normal distribution, the specific type of fault such as electrical, intermittent or freezing of the sensor can be determined to provide initial information as to the severity and type of remedial action required.

Sensor fault diagnostics and prognostics using component model and time scale orthogonal expansions

A method for detecting and predicting refrigerant level includes the steps of determining an estimated value for a parameter indicative of refrigerant level and comparing that estimated value to an actual value. The difference between the actual and estimated value provides a refrigerant charge indicator value. The charge indicator value is indicative of the amount of refrigerant contained within the system. A change value is combined with the charge indicator value to provide a prediction for the future value of the charge indicator value. This future value is determined based on a rate of change and charge indicator value over a selected period of time.

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Willimantic, CT, United States of America

Slaven Stricevic