Refrigerator manufacturers are continually challenged with improving energy efficiency and reducing the cost of the appliance simultaneously. Typically, refrigeration system components are optimized using isolated component models. This process is complimented with an experimental trial and error approach for final system level optimization. Also, optimization is carried out for a single objective by fixing other criteria to an acceptable level. This study will develop models and multi-objective optimization methodology which will allow the designer to optimize refrigeration components, namely heat exchangers, for cost and performance within a specified design space.;Since cost and performance are conflicting objectives, no single design will satisfy both simultaneously. The result of this search is a set of multiple optimum solutions called "Pareto Optimal Solutions". Air and refrigerant side correlations were combined with elemental approach to model the heat exchangers. Development of other components of the system such as the compressor, expansion device, and cabinet is presented. Detailed simulation models are typically complex and computationally demanding. An optimization algorithm requires several evaluations of such models. Response surface based metamodels for objective functions were used to save computational effort. A Genetic Algorithm based optimization tool is used for multicriteria optimization.;First, an analysis of a conventional single evaporator system is presented. Later, an experimental development of a dual evaporator system is presented. An optimization method similar to that of a single evaporator system is then applied to a dual evaporator system.
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