Geometry optimization of two-stage thermoelectric generators using simplified conjugate-gradient method

被引：81

作者：

Liu, Zhichun ^{[1
]}

Zhu, Shiping ^{[1
]}

Ge, Ya ^{[1
]}

Shan, Feng ^{[1
]}

Zeng, Lingping ^{[2
]}

Liu, Wei ^{[1
]}

机构：

[1] Huazhong Univ Sci & Technol, Sch Energy & Power Engn, Wuhan 430074, Peoples R China

[2] MIT, Dept Mech Engn, Cambridge, MA 02139 USA

来源：

APPLIED ENERGY | 2017年 / 190卷

基金：

中国国家自然科学基金;

关键词：

Thermoelectric generator; Power output; Conversion efficiency; Multi-objective; Multi-parameter; Optimization; HEAT-RECOVERY SYSTEM; MULTIPARAMETER OPTIMIZATION; PERFORMANCE OPTIMIZATION; POWER-GENERATION; ELECTRICAL LOAD; OPTIMAL-DESIGN; PEAK POWER; MODULE; SIMULATION; EXHAUST;

D O I：

10.1016/j.apenergy.2017.01.002

中图分类号：

TE [石油、天然气工业]; TK [能源与动力工程];

学科分类号：

0807 ; 0820 ;

摘要：

Thermoelectric devices can convert thermal energy directly into electrical energy. The aim of this study was to develop an approach for integrating computer-aided analysis with an optimization method that could be applied to the design and optimization of thermoelectric generators. The optimization framework consisted of a model generator, a direct solver, and a numerical optimizer. The simplified conjugate-gradient method (SCGM) was used to build the optimizer, and the general-purpose finite element code was used for the direct solver and model generator. This approach was applied to the multi-objective and multi-parameter optimization of geometric thermoelectric generators to design an optimal structure for both a two-stage bismuth-telluride (BiTe)-based and skutterudite-based thermoelectric generator (TEG) module. The leg length and the ratio between the cross-sectional areas (i.e., footprint) of the semiconductor columns and the TEG module were found to significantly affect the TEG performance; hence, all were incorporated into the present optimization study. Multi-objective optimization was used to realize a design that properly balanced the power output and conversion efficiency so that both improved simultaneously. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：540 / 552

页数：13

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