Geometric optimization of thermoelectric coolers in a confined volume using genetic algorithms

The demand for thermoelectric coolers (TEC) has grown significantly because of the need for a steady, low-temperature operating environment for various electronic devices such as laser diodes, semiconductor equipment, infrared detectors and others. The cooling capacity and its coefficient of performance (COP) are both extremely important in considering applications. Optimizing the dimensions of the TEC legs provides the advantage of increasing the cooling capacity, while simultaneously considering its minimum COP. This study proposed a method of optimizing the dimensions of the TEC legs using genetic algorithms (GAs), to maximize the cooling capacity. A confined volume in which the TEC can be placed and the technological limitation in manufacturing a TEC leg were considered, and three parameters––leg length, leg area and the number of legs––were taken as the variables to be optimized. The constraints of minimum COP and maximum cost of the material were set, and a genetic search was performed to determine the optimal dimensions of the TEC legs. This work reveals that optimizing the dimensions of the TEC can increase its cooling capacity. The results also show that GAs can determine the optimal dimensions according to various input currents and various cold-side operating temperatures.