Refrigerant charge affects the efficiency, capacity, and reliability of a heat pump, and incorrect charge can lead to increased energy consumption and decreased performance as well as potential damage to the system. Furthermore, refrigerant charge has an environmental impact, with high Global Warming Potential (GWP) refrigerants contributing to climate change. The HVAC&R society is adopting low-GWP refrigerants to alleviate the concern. For these reasons, accurate prediction of refrigerant charge is vital in designing heat pumps, particularly for low-GWP refrigerants; this charge prediction is done by charge models.

Meanwhile, existing charge models are limited in their charge prediction accuracy due to uncertainty in void-fraction models the charge models rely on for charge prediction. Experimental charge validation data can improve the accuracy of the charge model, but such data for low-GWP refrigerant charge is rare in the open literature.

The goal of this study is to address the issue by improving the accuracy of charge prediction; that is done by creating a high-accuracy charge model that is verified by experimental charge validation data. To gather this experimental charge data, a novel charge measurement method and charge measurement facility for measuring charge is created, resulting in high-fidelity experimental charge data for heat exchangers across various operating conditions of heat pumps. This database includes multiple refrigerants, including low-GWP refrigerants, R1234yf and R468C, and additional R410A as a reference. Employing this experimental data, a high-accuracy charge model is developed and validated, which is used to optimize the charge and cooling capacity of a heat pump simultaneously on a developed multi-objective optimization framework.