Optimization of segmented thermoelectric generator using Taguchi and ANOVA techniques

Ravi Anant Kishore,Shashank Priya,Mohan Sanghadasa

doi:10.1038/s41598-017-16372-8

Abstract

Recent studies have demonstrated that segmented thermoelectric generators (TEGs) can operate over large thermal gradient and thus provide better performance (reported efficiency up to 11%) as compared to traditional TEGs, comprising of single thermoelectric (TE) material. However, segmented TEGs are still in early stages of development due to the inherent complexity in their design optimization and manufacturability. In this study, we demonstrate physics based numerical techniques along with Analysis of variance (ANOVA) and Taguchi optimization method for optimizing the performance of segmented TEGs. We have considered comprehensive set of design parameters, such as geometrical dimensions of p-n legs, height of segmentation, hot-side temperature, and load resistance, in order to optimize output power and efficiency of segmented TEGs. Using the state-of-the-art TE material properties and appropriate statistical tools, we provide near-optimum TEG configuration with only 25 experiments as compared to 3125 experiments needed by the conventional optimization methods. The effect of environmental factors on the optimization of segmented TEGs is also studied. Taguchi results are validated against the results obtained using traditional full factorial optimization technique and a TEG configuration for simultaneous optimization of power and efficiency is obtained.

Highlights

Solid-state structure with no moving parts or harmful chemical discharge makes thermoelectric generators (TEGs) reliable, maintenance-free, and noiseless
The study by Hu et al reported that a segmented TEG module built using nanostructured PbTe- and BiTe-based materials had efficiency of 11% at temperature difference of 590 K, as compared to efficiency of 8.8% from a non-segmented TEG module made using just nanostructured PbTe material[15]
We study the effect of noise factors, namely ambient temperature and cooling coefficient, on the optimization of segmented TEG

Summary

Introduction

Solid-state structure with no moving parts or harmful chemical discharge makes TEGs reliable, maintenance-free, and noiseless. There have been extensive studies conducted in the last few decades in order to enhance the ZT of ( ) TE materials by increasing the power factor S2 and by reducing the thermal conductivity (κ) Some techniques, ρ such as nanostructuring, doping with Cu or Ag atoms, and adjusting atomic ratios, have been found to improve the ZT of TE materials[6,7,8,9,10,11,12,13,14]. Some of the state-of-the-art TE materials reported in literature are quantum-dot superlattice with ZT of 3.5 at 575 K by Harman et al.[16], thin film superlattice structure with ZT of 2.4 at 300 K and ZT of 2.9 at 400 K by Venkatasubramanian et al.[17], and lead antimony silver telluride (AgPbmSbTe2+m) with ZT of 2.2 at 800 K by Hsu et al.[18] These excellent laboratory results have not been transitioned into practical applications[19]. The study by Hu et al reported that a segmented TEG module built using nanostructured PbTe- and BiTe-based materials had efficiency of 11% at temperature difference of 590 K, as compared to efficiency of 8.8% from a non-segmented TEG module made using just nanostructured PbTe material[15]

Methods

Results

Conclusion