Hybrid ANN-PLS approach to scroll compressor thermodynamic performance prediction

In this paper, a scroll compressor thermodynamic performance prediction was carried out by applying a hybrid ANN-PLS model. Firstly, an experimental platform with second-refrigeration calorimeter was set up and steady-state scroll compressor data sets were collected from experiments. Then totally 148 data sets were introduced to train and verify the validity of the ANN-PLS model for predicting the scroll compressor parameters such as volumetric efficiency, refrigerant mass flow rate, discharge temperature and power consumption. The ANN-PLS model was determined with 5 hidden neurons and 7 latent variables through the training process. Ultimately, the ANN-PLS model showed better performance than the ANN model and the PLS model working separately. ANN-PIS predictions agree well with the experimental values with mean relative errors (MREs) in the range of 0.34-1.96%, correlation coefficients (R-2) in the range of 0.9703-0.9999 and very low root mean square errors (RMSEs). (C) 2014 Elsevier Ltd. All rights reserved.