Work

An Analytical Model for Performance Optimization of Thermoelectric Generator With Temperature Dependent Materials

Year: 2018

Type: article

Abstract: Accurate and efficient performance prediction of thermoelectric generators (TEG) is important for integrated and multi-parameter optimization especially in large-scale energy harvesting applications. In this paper, a comprehensive analytical model coupled with non-identical temperature-dependent material properties and effective heat transfer coefficient (EHTC) of both-sides heat exchangers is built to investigate the internal and external characteristics of the TEG. Parametric optimization of the TEG is carried out to maximize the output power and efficiency over a wide range of EHTCs, fill factor, and geometry of thermoelectric (TE) elements. The developed model can be efficiently solved by function solver (i.e. fsolve) in Matlab software, and its accuracy is validated with previous multi-physics numerical TEG model. The results show that statistical parameters of the TE element present non-linear behavior with variation of electrical load resistance. The optimal load ratio is larger than unit, and it reduces monotonically with increment of the cold-side EHTC, but changes inversely with the hot-side EHTC. For a fixed sum value of both-sides EHTCs, there are two different optimal ratios of the hot-side EHTC to the cold-side EHTC for maximum efficiency and power. In addition, the optimal length and cross-sectional area ratio of the TE elements are investigated with detailed analysis.

Source: IEEE Access

DOI: 10.1109/access.2018.2874947

Authors: Shaowei Qing, Alireza Rezaniakolaei, Lasse A. Rosendahl, Xiaolong Gou

Institutions: Chongqing University, Aalborg University

Language: English

Topic: Advanced Thermoelectric Materials and Devices

Subfield: Materials Chemistry

Field: Materials Science

Domain: Physical Sciences

SDG: Affordable and clean energy

Open Access status: gold

Estimated APC paid: $2,075