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

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 thermoelec...

Full description

Bibliographic Details
Main Authors: Ivan R. Cózar, Albert Massaguer, Eduard Massaguer, Andreu Cabot, Toni Pujol
Format: Article
Language:English
Published: Elsevier 2023-11-01
Series:Case Studies in Thermal Engineering
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2214157X23008900
Description
Summary: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.
ISSN:2214-157X