Thermo-mechanical optimization of thermoelectric generators using deep learning artificial intelligence algorithms fed with verified finite element simulation data

Chika Maduabuchi

Applied Energy, 2022, vol. 315, issue C, No S0306261922003622

Abstract: The rising levels of global warming in the environment owing to emissions from fossil-fuel-based engines has increased the search for efficient clean energy systems. Thermoelectric generators (TEGs) standout as a promising energy conversion device which can directly convert heat to electricity. Several optimization studies have been carried out on these devices to improve their power generation rate and efficiencies while guaranteeing long lifespan. However, the limitations of finite element methods (FEMs) in easily providing optimization guidelines at a fast rate has hindered the manufacture of TEGs with high thermo-mechanical performance.

Keywords: Artificial intelligence; Deep neural networks; Thermoelectric generator; Thermo-mechanical optimization; Operation lifespan (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (8)

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DOI: 10.1016/j.apenergy.2022.118943

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