Performance prediction of solid desiccant – Vapor compression hybrid air-conditioning system using artificial neural network

In the present study, ANN (artificial neural network) model for a solid desiccant – vapor compression hybrid air-conditioning system is developed to predict the cooling capacity, power input and COP (coefficient of performance) of the system. This paper also describes the experimental test set up for collecting the required experimental test data. The experimental measurements are taken at steady state conditions while varying the input parameters like air stream flow rates and regeneration temperature. Most of the experimental test data (80%) are used for training the ANN model while remaining (20%) are used for the testing of ANN model. The outputs predicted from the ANN model have a high coefficient of correlation (R > 0.988) in predicting the system performance. The results show that the ANN model can be applied successfully and can provide high accuracy and reliability for predicting the performance of the hybrid desiccant cooling systems.

[1]  W. A. Beckman,et al.  Hybrid desiccant cooling systems in supermarket applications , 1985 .

[2]  Orhan Büyükalaca,et al.  Experimental investigation of a novel configuration of desiccant based evaporative air conditioning system , 2013 .

[3]  Kemal Atik,et al.  Performance parameters estimation of MAC by using artificial neural network , 2010, Expert Syst. Appl..

[4]  John W. Mitchell,et al.  The Use of Dehumidifiers in Desiccant Cooling and Dehumidification Systems , 1986 .

[5]  M. Hosoz,et al.  Artificial neural network analysis of an automobile air conditioning system , 2006 .

[6]  Kemal Atik,et al.  Modeling of a mechanical cooling system with variable cooling capacity by using artificial neural network , 2007 .

[7]  Z. Lavan,et al.  Performance of a Cross-Cooled Desiccant Dehumidifier Prototype , 1982 .

[8]  Terry R. Penney,et al.  Desiccant cooling: State-of-the-art assessment , 1992 .

[9]  Pradeep K. Sahoo,et al.  Optimization of cooling load for a lecture theatre in a composite climate in India , 2011 .

[10]  Haslinda Mohamed Kamar,et al.  Artificial neural networks for automotive air-conditioning systems performance prediction , 2013 .

[11]  S. C. Kaushik,et al.  Evaluation of solid-desiccant-based evaporative cooling cycles for typical hot and humid climates , 1995 .

[12]  M. Hosoz,et al.  Performance prediction of a cooling tower using artificial neural network , 2007 .

[13]  Manish Mishra,et al.  Performance studies of hybrid solid desiccant-vapor compression air-conditioning system for hot and humid climates , 2015 .

[14]  R. S. Barlow Analysis of the adsorption process and of desiccant cooling systems: A pseudo- steady-state model for coupled heat and mass transfer , 1982 .

[15]  Wilfrido Rivera,et al.  Optimal COP prediction of a solar intermittent refrigeration system for ice production by means of direct and inverse artificial neural networks , 2012 .

[16]  Irene P. Koronaki,et al.  Thermodynamic analysis of an open cycle solid desiccant cooling system using Artificial Neural Network , 2012 .

[17]  Manish Mishra,et al.  Performance analysis of hybrid solid desiccant–vapor compression air conditioning system in hot and humid weather of India , 2016 .

[18]  Manish Mishra,et al.  Solid desiccant air conditioning – A state of the art review , 2016 .

[19]  Refrigerating ASHRAE handbook of fundamentals , 1967 .

[20]  Zhen Tian,et al.  Electric vehicle air conditioning system performance prediction based on artificial neural network , 2015 .

[21]  S. A. Sherif,et al.  A feasibility study of a solar desiccant air-conditioning system—Part I: psychrometrics and analysis of the conditioned zone , 1999 .

[22]  Arif Hepbasli,et al.  Experimental investigation of a novel desiccant cooling system , 2010 .

[23]  M. Mohanraj,et al.  Applications of artificial neural networks for refrigeration, air-conditioning and heat pump systems—A review , 2012, Renewable and Sustainable Energy Reviews.

[24]  Kamaruzzaman Sopian,et al.  Artificial neural network analysis of liquid desiccant dehumidifier performance in a solar hybrid air-conditioning system , 2013 .

[25]  P. J. Banks,et al.  Coupled quilibrium heat and single adsorbate transfer in fluid flow through a porous medium—I Characteristic potential and specific capacity ratios , 1972 .

[26]  I. L. Maclaine-Cross Proposal for a hybrid desiccant air-conditioning system , 1988 .

[27]  Manish Mishra,et al.  Performance prediction of rotary solid desiccant dehumidifier in hybrid air-conditioning system using artificial neural network , 2016 .