Multi-objective optimization of thermoelectric cooler using genetic algorithms

Abstract

The thermoelectric cooler (TEC) is a kind of cooling equipment which used to dissipate heat from the devices by Peltier effect. The cooling capacity (Qc) and coefficient of performance (COP) are both significant performance parameters of a thermoelectric cooler. In this article, three-dimensional numerical simulations are carried out by finite element analysis based on the temperature-dependent materials properties. The experimental and geometrical parameters have important effects on the TEC performance which have been analysed, such as electrical current, geometric configuration of thermoelectric leg, Thomson effect, thermal contact resistances and electrical contact resistances. The results show when the Thomson effect is ignored, the maximum difference in the cooling capacity is 7.638 W while the maximum difference in the COP is 0.09. When contact effect is not considered, the maximum difference in the cooling capacity is 22.06 W while the maximum difference in the COP is 0.75. Furthermore, the cooling capacity and COP have also been simultaneously optimized according to the multi-objective genetic algorithm. The best optimal value is obtained making use of TOPSIS (technique for order preference by similarity to an ideal solution) method from Pareto frontier. Investigated on these optimal design parameters which were anticipated to provide real guidance in industry.

A review on recent opportunities in MATLAB software based modelling for thermoelectric applications

“…The loss to thermal conductance of 1/Ktem and 1/Kp is shown in the [7,11,12,33,35,38,44,54]. Likewise for 2 nd stage of TEG are optimized by decision making methods such as fuzzy, LINMAP and TOPSIS [9,18,40,43]. The resultant outcomes are 3.3 ≤ TEG (%) ≤ 6.1, 0.045 ≤ entropy-TEG ≤ 0.071 and 1.48W ≤ power ≤ 3.80W for different algorithms is shown in the fig.…”

Micro thermoelectric devices: From principles to innovative applications

“…[4,5] In addition to the aspect of thermoelectric materials, more factors should be considered for the device design to reach the prescribed performance (conversion efficiency for TEGs and coefficient of performance for TECs), for instances, the geometric configuration of thermoelectric pairs, thermal and electrical contact resistances, and so on. [6] Advances in modern technology have consistently pushed the miniaturization of electronic devices or systems and brought more opportunities for commercial profit. [7] The traditional evolutionary engineering effort (i.e., cutting process) to reduce size suffers from inefficient delivery and/or precision limit of several hundreds of micrometers.…”