A regression-based approach for the explicit modeling of simultaneous heat and mass transfer of air-to-refrigerant microchannel heat exchangers

With the increasing utilization of mathematical models for heat exchanger optimization studies, there lies the demand for robust and accurate yet fast modeling methodologies on the simultaneous heat and mass transfer process. This research conducted an in-depth review of mathematical models for heat exchanger performance prediction. We categorized typical modeling methodologies into lumped models, zone models, and numerical methods. The review of mathematical models revealed the iterative approaches for performance prediction of fully wet conditions are computationally expensive. Also, the assumptions and derivations based on adiabatic fin tips do not allow flexibility with advanced fin designs. In order to address these two issues, this research developed a systematic regression approach under a common range of geometrical and thermal parameters under both wet and dry conditions, single-phase and two-phase refrigerant flow. Such regression analysis provides an explicit calculation procedure for micro-channel heat exchangers' performance prediction. The improved semi-regression models show advances in accuracy and calculation speed within the selected ranges of geometries and working conditions for heat pump applications.