Abstract—Thermo-electric Coolers nowadays are applied in a wide range of thermal energy systems. Over the past decades, many researches were employed to improve the efficiency of TECs by enhancing the material parameters and design parameters. The material parameters are the most significant, but they are restricted by currently available materials and module fabricating technologies. Therefore, the main objective of TECs design is to determine a set of design parameters such as leg area, leg length and the number of legs. In this paper, a new method of optimizing the dimension of TECs using hybrid simulated annealing genetic algorithm to maximize the rate of refrigeration was proposed. Equality constraint and inequality constraint were taken into consideration. The results of optimization obtained by using Hybrid Simulated Annealing Genetic Algorithm are validated by comparing with those obtained by simulated annealing and Cheng’s work using genetic algorithm. This work revealed that Hybrid Simulated Annealing Genetic Algorithm is more robust and more reliable than genetic algorithm and simulated annealing. 
 

Index Terms—thermo-electric coolers, simulated annealing, genetic algorithm, rate of refrigeration, design parameters

Cite: Doan V. K. Khanh, Pandian M. Vasant, Irraivan Elamvazuthi, and Vo N. Dieu, "Geometric Optimization of Thermo-Electric Coolers Using Hybrid Simulated Annealing Evolutionary Algorithm," International Journal of Electronics and Electrical Engineering, Vol. 4, No. 5, pp. 412-415, October 2016. doi: 10.18178/ijeee.4.5.412-415