Journal of Refrigeration, Air conditioning, Heating and ventilation Original Research
Metaheuristic-Based Enhancement of Cooling Capacity in Miniaturized Thermoelectric Refrigeration Systems
Abstract
Because of its small size, dependability, silent operation, and appropriateness for precise thermal management to electronic and portable cooling applications, miniaturized thermoelectric refrigeration systems have received a lot of attention. However, geometrical limitations, electrical losses, and difficulties with heat dissipation frequently limitations their cooling capacity. In order to better understand and improve the cooling performance of miniature refrigeration systems, this work offers a thorough model for mathematics of a single-stage thermocouple cooler (TEC). In order to accurately forecast system performance under limited operating conditions, the model integrates significant thermoelectric phenomena with pragmatism factors such electrical contact opposition and hot-side thermal immunity. Two metaheuristic optimization algorithms—Genetic Algorithm (GA) and simulator annealing (SA)—are used to maximize the cooling capacity, which is represented in terms of the rate of chilling (ROR). The thermoelectric elements' geometric design parameters and input current are taken take into account as choice variables by the optimization system. These methods are used to find the best design combinations that can improve cooling efficiency while preserving the small size needed for tiny workloads. The findings show that by discovering nearly ideal combinations of structural and operating factors, both metaheuristic techniques successfully boost TEC's cooling capability. When compared to traditional arrangements, the improved designs produce a significant boost in ROR. Additionally, the solutions derived from GA and SA show strong agreement, demonstrating the security and dependability of the optimization procedure. The GA offers several workable optimal solutions, providing more flexibility in practical design selection without sacrificing cooling effectiveness, even though both approaches achieve comparable performance improvements. The suggested metaheuristic-based optimization approach promotes the use of high-performance scaled thermoelectric refrigeration systems in cutting-edge thermal management technologies and offers an advantageous structure for their development.
Keywords
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