Abstract
This study presents a new approach using genetic algorithms (GAs) to optimize the arrangement of two-stage thermoelectric coolers (TECs). Focusing on the two-cascade TECs, parameters, the applied electrical current and the number of thermocouples in each stage, were optimized to yield the maximum cooling capacity and the maximum coefficient of performance (COP). Based on the target cold-side temperature, the optimal arrangement of each type of two-stage TECs was found and the maximum cooling capacity and the maximum COP were thus reached.
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