SINE COSINE OPTIMIZATION-BASED APPROACH FOR OPTIMIZING THERMOELECTRIC MODULES IN WASTE HEAT RECOVERY SYSTEMS (Global Journal of Advanced Engineering Technologies and Sciences, 2025)
In this paper, the topic of thermoelectric modules (TEMs) optimization in waste heat recovery systems is discussed, and it is addressed on the optimization of power to the maximum and efficiency to the optimum. The new strategy of employing the Sine Cosine Optimization (SCO) algorithm is proposed to optimize the most important parameters of TEMs, including length and cross-sectional area of thermoelectric legs. The objective of the study is to overcome the drawback of the conventional optimization methods, which include the Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), as they are time-consuming and inconvenient with respect to making real-time changes. Using dynamic adjustment of the dimension of thermoelectric legs according to certain temperature gradients, SCO algorithm will help to improve the functionality of TEMs in reality. The simulation results indicate that the SCO-optimized TEM is superior to the base TEM, giving it power generation enhancing results, where the output becomes 33% more with optimal current amounts. The study is a suggestive solution to the enhancement of thermoelectric waste heat recovery systems effectiveness and fastidiousness.