Thermodynamic modelling and performance optimization of trapezoidal thermoelectric cooler using genetic algorithm

The thermoelectric coolers (TECs) are being used widely in cooling of many electronic devices because of their stable operation. The cooling capacity and energy efficiency are two important performance parameter of a thermoelectric cooler (TEC) which can also be enhanced by changing the geometric configuration of thermoelectric leg. In this study, firstly, thermodynamic model of an exoreversible thermoelectric cooler based on first and second laws having trapezoidal shaped thermoelectric leg has been developed considering the Thomson effect. Modified expressions are derived analytically for dimensionless cooling load, energy and exergy efficiencies, dimensionless figure of merit and dimensionless irreversibilities including Thomson effect. The effects of temperature ratio (T-c/T-h) and shape parameter (A(c)/A(h)) on the performance parameters have been studied. Secondly, the cooling capacity and energy efficiency have been optimized using the genetic algorithm (GA). The optimal parameters obtained through GA optimization process, corresponding to maximum cooling capacity and maximum energy efficiency have been compared with the optimal parameters obtained through analytical method which proved the validity of GA optimization method for optimization of TEC. After the testing, the GA optimization has been performed to find out the optimum parameters corresponding to maximum cooling load and maximum energy efficiency. It was found that the GA population converges quickly after 30 runs only which proved the GA as the time and cost effective optimization tool. Also, the Thomson effect improves the cooling capacity of the TEC. Thus, for a practical TEC, the operating and geometric parameters should be chosen to achieve maximum cooling capacity and energy efficiency.