Comparison of approximation-assisted heat exchanger models for steady-state simulation of vapor compression system. (5th February 2020) - Huang, Ransisi; Ling, Jiazhen; Aute, Vikrant
Highlights: An approach to speed up steady-state vapor compression system simulation is presented. 3 heat exchanger approximation models were compared for accuracy and speed. Kriging-based models were the best with mean absolute capacity error of 0.9%. Mean absolute error in coefficient of performance for Kriging models was 1.6%. The on-the-fly approximation models resulted in simulation speed up of 10–600×. Abstract: Finite-volume heat exchanger models are generally the most time-consuming component in a Component-based Vapor Compression Cycle simulation. While the approach of Performance Maps is commonly used, this method has its limitations. This study compares 3 approximation-assisted heat exchanger (HX) models for the steady-state simulation of vapor compression system: interpolation black-box model, Kriging black-box model, and Kriging-assisted three-zone model. We applied the 3 models to approximate the pressure drop (Δ P ) and enthalpy change (Δ h ) of five different HXs at ten-thousand refrigerant inlet conditions randomly selected from the respective input domains of the HXs. Moreover, we applied the 3 models to simulate three different vapor compression systems at various test conditions. The approximation results were compared against the baseline finite-volume results. The results show that, for approximation of HX performance, Kriging metamodel gave the most accurate approximation with an overall Δ P and Δ h mean absolute error (MAE) of 4.46% and 0.9%, respectively. For system simulations, Kriging metamodel gave the most accurate results. Its largest COP and capacity errors were 2.54% and 1.45%, respectively. The results also show that the three-zone model gave large error for Δ h approximation at those operating conditions where the HX had an average two-phase outlet condition (xout, avg  < 1.0) but with superheated vapor in part of the coil (vap% > 0). For computational efficiency, by using the approximation-assisted models, the system simulation time was sped up by a factor of 10 to 600, depending on the testing conditions.