A Statistical Analysis of Desiccant Dehumidifier for Air Conditioning Application

Due to the direct utilization of thermal energy and possibility of using renewable energy resources, the interest of using desiccant wheels for air-conditioning application is increasing rapidly. The thermally driven desiccant cooling systems are environmental friendly and has a great potential to reduce the peak electricity demand. During the experiments the inlet and outlet parameters in the dehumidifier can be easily measured. However, in theoretical analysis it is difficult to predict the relationship between these parameters because of the complexity of combined heat and mass transfer process. In this paper a statistical analysis using Minitab software is used to predict the functional relationships between the input and output parameters in the dehumidifier. The factorial analysis is first carried out to eliminate the factors which does not affect the response, significantly. Then, the regression analysis is carried out to analyze the effect of significant operating variables (independent) on the moisture absorption rate in the dehumidifier and to develop a relationship between dependent and independent variables. Regression analysis shows that the inlet air humidity ratio, ratio of mass flow rates, and regeneration temperature cause significant variation (P<0.01) in the absorption rate.