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Data de publicació

2023-10-18

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cc-by (c) Cozar Ivan R. et al., 2023
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/219448

Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis

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Recurs relacionat

https://doi.org/10.1016/j.csite.2023.103584

Resum

A methodology to determine the most influential independent input variables on the maximum power generation of an automotive thermoelectric generator is developed. A validated numerical model is used to predict the maximum power generation of a thermoelectric generator composed of several thermoelectric modules installed in the exhaust pipe of an internal combustion engine. The Morris sensitivity analysis and the least absolute shrinkage and selection operator feature selection approach are employed to identify the most influential variables. The amount of independent variables selected to carry out the analysis are 18 and they are embedded in different fields such as hydraulic, thermal, electrical, chemical, geometrical and design. Results show that the most influential variables are the inlet temperature of the hot fluid and the Seebeck coefficient and electric resistance of the thermoelectric modules. The thickness of the thermoelectric modules has the least influence on the maximum power generation. These findings could be useful to other researchers to develop simpler mathematical models without compromising the accuracy.

Matèries

Termoelectricitat, Contaminants, Generadors elèctrics

Matèries (anglès)

Thermoelectricity, Pollutants, Electric generators

Citació

Col·leccions

Articles publicats en revistes (Ciència dels Materials i Química Física)

Citació

COZAR, Ivan R., et al. Identification of the most influential variables on the power generation of an automotive thermoelectric generator through a global sensitivity analysis. Case Studies In Thermal Engineering. 2023. Vol. 51. [consulted: 18 of August of 2026]. Available at: https://hdl.handle.net/2445/219448

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