Optimal design of adsorption chillers based on a validated dynamic object-oriented model

The design of adsorption chillers is usually based on experience and high experimental effort. Experimental effort can be reduced by using dynamic models. In the present study, a dynamic model is validated with a modular adsorption chiller test bed and then used to optimize design and process parameters to gain maximum cooling power. The modularity of the test bed enables the exchange of single components without changing the remaining setup. This modular structure is also reflected in the object-oriented dynamic model. Model calibration is based on the heat flows of all components. This measure allows the gain of deep insight into the system behavior and a quantitative comparison of model accuracy. The calibrated model is validated by predicting the system behavior for different operating conditions and also changed adsorbent materials. Adsorbent materials silica gel 123 and zeolite 13X are investigated. Operating points vary in cycle time, as well as temperatures of evaporation, adsorption, and desorption. The model exhibits excellent prediction capability for the coefficient of performance and for the cooling power. The modular setup of the model is then used for targeted optimization of the adsorption system; the cycle time and the sizing of the heat exchangers are rigorously optimized, leading to adsorption chillers with maximum cooling power.

[1]  Takao Kashiwagi,et al.  Study on a re-heat two-stage adsorption chiller – The influence of thermal capacitance ratio, overall thermal conductance ratio and adsorbent mass on system performance , 2007 .

[2]  Tomas Núñez,et al.  Modelling of an adsorption chiller for dynamic system simulation , 2009 .

[3]  Bidyut Baran Saha,et al.  Waste Heat Driven Multi-Bed Adsorption Chiller: Heat Exchangers Overall Thermal Conductance on Chiller Performance , 2006 .

[4]  Hui Tong Chua,et al.  A comparative evaluation of two different heat-recovery schemes as applied to a two-bed adsorption chiller , 2007 .

[5]  Alessio Sapienza,et al.  A dynamic multi-level model for adsorptive solar cooling , 2011 .

[6]  Manuel Gräber Energieoptimale Regelung von Kälteprozessen , 2013 .

[7]  Takao Kashiwagi,et al.  Parametric study of a two-stage adsorption chiller using re-heat - The effect of overall thermal conductance and adsorbent mass on system performance , 2006 .

[8]  E. Iso,et al.  Measurement Uncertainty and Probability: Guide to the Expression of Uncertainty in Measurement , 1995 .

[9]  José M. Corberán,et al.  Modelling of an adsorption system driven by engine waste heat for truck cabin A/C. Performance estimation for a standard driving cycle , 2010 .

[10]  Jung-Yang San,et al.  Testing of a lab-scale four-bed adsorption heat pump , 2014 .

[11]  V. V. Serpinskii,et al.  Adsorption in micropores , 1967 .

[12]  Hui Tong Chua,et al.  Two bed silica gel - water adsorption chillers: An effectual lumped parameter model , 2007 .

[13]  F. Meunier,et al.  Predictive model and experimental results for a two-adsorber solid adsorption heat pump , 1988 .

[14]  J. P. Zhang,et al.  Simulation of operating characteristics of the silica gel–water adsorption chiller powered by solar energy , 2011 .

[15]  Mahmudur Rahman,et al.  A numerical analysis of cooling water temperature of two-stage adsorption chiller along with different mass ratios , 2011 .

[16]  Hans Bock,et al.  Determining the optimum cyclic operation of adsorption chillers by a direct method for periodic optimal control , 2011 .

[17]  Takao Kashiwagi,et al.  Computational analysis of an advanced adsorption-refrigeration cycle , 1995 .

[18]  E. Schmidt Wärmeübergang und Druckverlust in Rohrschlangen , 1967 .

[19]  Ruzhu Wang,et al.  Study of the fundamentals of adsorption systems , 1997 .

[20]  Ruzhu Wang,et al.  Study on a silica gel–water adsorption chiller integrated with a closed wet cooling tower , 2010 .

[21]  Peter A. Fritzson,et al.  Principles of object-oriented modeling and simulation with Modelica 2.1 , 2004 .

[22]  E. Glueckauf,et al.  Theory of chromatography. Part 10.—Formulæ for diffusion into spheres and their application to chromatography , 1955 .

[23]  Joachim Luther,et al.  Influence of Adsorbent Characteristics on the Performance of an Adsorption Heat Storage Cycle , 2003 .

[24]  Wilhelm Tegethoff,et al.  Modelling of heat pumps with an object-oriented model library for thermodynamic systems , 2010 .

[25]  Joachim Weiss,et al.  Theory of Chromatography , 2007 .

[26]  Dirk Schawe,et al.  Theoretical and experimental investigations of an adsorption heat pump with heat transfer between two adsorbers , 2001 .

[27]  Franz Lanzerath,et al.  Combination of finned tubes and thermal coating for high performance water evaporation in adsorption heat pumps , 2014 .

[28]  Ruzhu Wang,et al.  Capillary-assisted flow and evaporation inside circumferential rectangular micro groove , 2009 .

[29]  Vincent Goetz,et al.  Influence of Microporous Characteristics of Activated Carbons on the Performance of an Adsorption Cycle for Refrigeration , 1996 .

[30]  Christopher Yu Hang Chao,et al.  Performance analysis of a waste heat driven activated carbon based composite adsorbent – Water adsorption chiller using simulation model , 2012 .

[31]  Takahiko Miyazaki,et al.  The performance analysis of a novel dual evaporator type three-bed adsorption chiller , 2010 .