Modeling and dehumidification capacity prediction of polymer desiccant wheels
To effectively predict the dehumidification performance of a PDW(polymer desiccant wheel),two methods including the effectiveness method model and the BP neural network model were employed.The model of the PDW was constructed with experimental data from 47 different cases and was compared with data from additional 20 scenarios.The results illustrate that both models can effectively regress the 47 sets of experimental data and the error between predicted data and experimental data from the additional 20 sets is minimal.Furthermore,the effectiveness method model exhibits higher accuracy in predicting the air outlet temperature,while the BP neural network model performs better in predicting the air outlet humidity.Additionally,Guangzhou,Shanghai,Wuhan,and Beijing were selected to investigate the dehumidification capacity of the PDW operating during the cooling season in different climate zones.The results reveal that the PDW achieves its highest performance in Guangzhou,followed by Shanghai,Wuhan,and lastly Beijing.
万方数据
维普
