Material Property Characterization and Parameter Estimation of Thermoelectric Generator by Using a Master–Slave Strategy Based on Metaheuristics Techniques

Daniel Sanin-Villa, Oscar Danilo Montoya and Luis Fernando Grisales-Noreña ()
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Daniel Sanin-Villa: Departamento de Mecatrónica y Electromecánica, Instituto Tecnológico Metropolitano, Medellín 050036, Colombia
Oscar Danilo Montoya: Grupo de Compatibilidad e Interferencia Electromagnética (GCEM), Facultad de Ingeniería, Universidad Distrital Francisco José de Caldas, Bogotá 110231, Colombia
Luis Fernando Grisales-Noreña: Department of Electrical Engineering, Faculty of Engineering, Universidad de Talca, Curicó 3340000, Chile

Mathematics, 2023, vol. 11, issue 6, 1-19

Abstract: Thermoelectric generators (TEGs) have gained significant interest as a sustainable energy source, due to their ability to convert thermal energy into electrical energy through the Seebeck effect. However, the power output of TEGs is highly dependent on the thermoelectric material properties and operational conditions. Accurate modeling and parameter estimation are essential for optimizing and designing TEGs, as well as for integrating them into smart grids to meet fluctuating energy demands. This work examines the challenges of accurate modeling and parameter estimation of TEGs and explores various optimization metaheuristics techniques to find TEGs parameters in real applications from experimental conditions. The paper stresses the importance of determining the properties of TEGs with precision and using parameter estimation as a technique for determining the optimal values for parameters in a TEG mathematical model that represent the actual behavior of a thermoelectric module. This methodological approach can improve TEG performance and aid in efficient energy supply and demand management, thus reducing the reliance on traditional fossil fuel-based power generation.

Keywords: thermoelectric generators; modelling and parameter estimation; optimization meaheuristic techniques; smart grids (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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