Optimizing the Arrangement of Two-Stage Thermoelectric Coolers through a Genetic Algorithm

Abstract

This study presents a new approach that uses a genetic algorithm (GA) to optimize the arrangement of two-stage thermoelectric coolers (TECs). Three practical configurations of two-stage TECs, 1) with two stages electrically connected in series, 2) with two stages electrically separated from each other and 3) with two stages electrically connected in parallel, were studied. Parameters, the applied electrical current and the number of thermocouples in each stage, were optimized to maximize the cooling capacity and the coefficient of performance (COP). The optimal parameters of each two-stage TECs were determined for each target cold-side temperature, and the maximum cooling capacity and the maximum COP were thus reached. The results of the optimization show that the electrically separated two-stage TECs yield the maximum cooling capacity, whereas the two-stage TECs that are electrically connected in series and electrically separated both produce the maximum COP. The optimal design of two-stage TECs can be realized using GA, and this method has considerable potential in designing a complex TEC system.