Influence of equations of state and mixture models on the design of a refrigeration process

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

Abstract

In refrigeration technology, there is a need for alternative refrigerants that need to fulfill several requirements, such as low (or no) global warming potential, flammability, ozone depletion potential, and toxicity. While there are many substances available that could potentially be used as refrigerants, only relatively few meet all of the requirements. Pure alternative refrigerants have been studied quite extensively in the past. However, mixtures (blends) of refrigerants are not that well-studied. One of the reasons for this is that the prerequisite for an extensive screening of refrigerant mixtures is the availability of reliable predictive mixture models. In this work, we investigate typically used mixture models for a simple refrigeration cycle (split air conditioner with internal heat exchanger) and compare their predictive performance with the results of reference multi-fluid mixture models for three binary mixtures with different mixing behavior, i.e., R-410a, R-421a, and R-507a. We found that regarding coefficient of performance (COP), heat exchanger performance parameter, and volumetric cooling capacity, the largest differences between the models have been observed in the prediction of the heat exchanger performance parameter. For the studied systems, the COP and heat exchanger performance parameter are mostly influenced by the pure fluid equations of state used, while the volumetric cooling capacity depends more on the choice of the mixture model. Furthermore, some models yield results for some of the studied performance parameters that are in very good agreement with the reference model, although the prediction of thermophysical properties deviates significantly from the reference model.

Details

Original languageEnglish
Pages (from-to)193-205
Number of pages13
JournalInternational Journal of Refrigeration
Volume121
Publication statusPublished - Jan 2021
Peer-reviewedYes

External IDs

ORCID /0000-0001-7908-4160/work/168204400

Keywords

Keywords

  • Air-conditioning unit, Cubic equation of state, Lee-Kesler-Plöcker, Multi-fluid mixture model, PCP-SAFT, Predictive mixture model