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.
Highlights
It is of more importance to achieve thermal management of electronic devices
Amin et al.12 considered cooling capacity and coefficient of performance (COP) of the TEC as double objective functions. They showed that the chemical reaction (CRO) algorithm can be effectively applied in optimal design of twostage thermoelectric cooler
The TEC model consists of seventy-one pairs of P-N legs connected with copper conductors
Summary
It is of more importance to achieve thermal management of electronic devices. Optimizing the geometry structure of TEC is an effective method to improve the cooling capacity and COP of TEC. Amin et al. considered cooling capacity and COP of the TEC as double objective functions They showed that the chemical reaction (CRO) algorithm can be effectively applied in optimal design of twostage thermoelectric cooler. Lamba et al. optimized performance of trapezoidal thermoelectric cooler using genetic algorithm including Thomson effect and thermal contact resistances. The most of above studies used zero-dimensional model to obtain the analytical solution of TEC performance, its accuracy is low attribute to many simplifying assumptions These studies ignore the effect of Thomson effect or assume Thomson effect to be symmetrically distributed in thermoelectric elements in combination with optimization algorithm. The optimization approach used and the solution results are anticipated to provide a favor to the real TEC design
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