Compressor is A Sensor

Abstract

The performance of the heat pump system varies greatly depending on the refrigerant charge amount. Improving the refrigerant charge fault detection and diagnostics (FDD) method of vapor compression systems have the potential for increasing energy efficiency and reducing service cost. Previous studies to predict refrigerant charge amount are mostly empirical methods which require significant amount of experimental data for high accuracy. The primary goal of this research is to develop a charge fault detection method which requires only a few experimental data with high prediction accuracy. Currently, pump down operations are typical practices by HVAC technicians when they need to open the refrigerant circuit to make a repairment. When pumping down, a valve at the liquid line would close to stop the refrigerant flow, and the refrigerant is pumped by the compressor from the evaporator side to the condenser side. By monitoring the real time suction/discharge pressures and temperatures, the refrigerant mass at the evaporating and condensing sides can be accurately calculated. Therefore, it is important to conduct dynamic simulation of the pump-down operation. In this project, ORNL partnered with the Helix Innovation Center in Copeland LLC developed a model to simulate the pumping down process. The simulation is driven by DOE/ORNL Heat Pump Design Model (HPDM) [1]. The model successfully captured the dynamics of system during pump-down operation and the result is reviewed and validated by the test data. Secondly, the project team validated the pump-down based charge prediction method via experiment on a 3-ton residential R410A split heat pump system. The experiments were conducted at three different charge levels, i.e., 7 lbm, 8 lbm, and 9 lbm. At each charge level, the pump down operations were conducted for four different outdoor conditions. For the same charge level and the same outdoor temperature, the pump-down operations were repeated three times. The charge prediction method innovatively utilizes the compressor low-pressure cut-off protection and the compressor performance map. Two charge prediction methods are validated. The first method is based on the prediction of charge migration in the compressor during the pump-down process, and the second method is based on the usage of detailed heat exchanger model with inputs from quasi-steady-state operation at the end of pump-down. Thirdly, the charge prediction method was validated on a 4-ton light commercial packaged roof-top heat pump with by manually closing a valve on the liquid line at system steady-state operation mode and system stand-by mode. The experiments were conducted at four different charge levels, i.e., 8 lbm, 9 lbm, 10 lbm and 11 lbm. At each charge level, the pump-down operations were conducted for four different outdoor conditions. As a result of validation, the deviation of the charge prediction method based on refrigerant mass migration during the pump-down process is within 10% for residential split heat pump system, and the deviation of the charge prediction method using detailed heat exchanger model and quasi-steady-state data at the end of pump-down is within 6% for both residential split system and light commercial packaged roof-top heat pump system.