Maximisation of energy and exergy efficiencies for a sustainable thermoelectric cooling system by applying genetic algorithm

摘要

The efficient thermal management of thermoelectric cooler (TEC) as a sustainable cooling technology is important. The energy loss, electrical power requirement, and irreversibility of the TEC need to be minimised. Through this work, authors separately optimised TEC energy efficiency (eta(I)) and exergy efficiency (eta(II)) considering thermoelectric elements geometry and electric current by using the genetic algorithm (GA). The effects of electrical contact resistance and thermal resistance are considered in the mathematical model. Unlike previously reported works, the authors have used junction temperatures different from surface temperatures at the respective cold and hot sides of TEC. This study reveals that maximum energy and exergy efficiencies are obtainable at the same values of electric current, length, and cross-sectional area of thermoelectric elements. At cold surface temperature (T-c) of 20 degrees C, the maximum energy efficiency of 4.11 and the maximum exergy efficiency of 0.0715 are obtained. GA result is validated through ANSYS (R) finite-element simulation.