Application of genetic algorithm to maximizing the cooling capacity in a thermoelectric cooling system

Thermoelectric cooling (TEC) system has grown significantly because of the need for a steady, low-temperature operating environment for numerous electronic devices. The cooling capacity of the TEC system should be maximized in considering applications. The TEC system usually consists of a TEC device and an external hot-side heat exchanger. While the heat transfer effect of the hot-side heat exchanger is limit, the optimization of the dimensions of thermoelectric elements could increase the cooling capacity. This study proposed a novel approach of optimizing the dimensions of thermoelectric elements via genetic algorithm (GA), to maximize the cooling capacity. Parameters, including the element length, the element area and the number of elements, were taken as the variables. The results show that GA can determine the optimal dimensions while the heat transfer effect of the hot-side heat exchanger is considered