Simultaneous optimization of four parameters in the stack unit of a thermoacoustic refrigerator

Abstract

Thermoacoustic refrigerators are environmentally friendly cooling systems that use no refrigerants. Optimization of the performance of any cooling system is crucial for an efficient energy management. Most of the optimization techniques in thermoacoustic systems utilized to date involved experimental and numerical parametric studies which are generally limited to the variations of the parameters to be optimized at discrete values. This study reports on the optimization of a thermoacoustic refrigerator using multi-objective genetic algorithm (MOGA). The study introduces the ability of MOGA to optimize four different variables which are length of stack, center position of stack, blockage ratio and drive ratio simultaneously. The four variables are optimized to achieve the two objectives; a maximum cooling and minimum acoustic power required at the stack and provide the optimum coefficient of performance, COP. The results show that the optimum COP = 1.35 with a cooling power of Qc = 6.57 W, acoustic power of Wn = 4.86 W and with the resonator diameter of D = 3.8 cm.