Distributed parameter modeling and its application in parallel flow condenser optimization design based on genetic algorithm

Abstract

A parallel flow (PF) condenser with mini-channels is commonly used as a condenser in automobile air-conditioning systems. A distributed parameter model (DPM) for the PF condenser (4 passes with 15, 6, 4, and 3 tube numbers, hydraulic diameter Dh = 1.7 mm) was developed based on classical correlations of heat transfer and flow friction. Experiments were performed to investigate the thermal hydraulic performance of PF condenser. The proposed DPM model was verified by experimental data. The optimal design of the PF condenser based on DPM was carried out with heat transfer and pressure drop taken as two objective functions. Genetic algorithm (GA) was utilized to solve the multi-objective problem. The hydraulic diameter and the tube numbers of each pass were chosen as design parameters. Pareto optimal solutions for the PF condenser were obtained. Analyses of variation in hydraulic diameter and tube numbers of the PF condenser are also presented.