Multi-parameter optimization and uncertainty analysis of multi-stage thermoelectric generator with temperature-dependent materials

Energy Reports

Zhi-Zhu He¹  Tao Yin²  Wen-Tao Li²  Ke Li² 

[1] Correspondence to: 17 Qinghua Donglu, China Agricultural University, Beijing 100083, China.;Department of Vehicle Engineering, College of Engineering, China Agricultural University, Beijing 100083, China;

关键词: Multi-stage TEG;    Thermoelectric performance;    Uncertainty analysis;    Geometry optimization;    Impedance matching condition;   

DOI  :  

来源: DOAJ

【 摘 要 】

It plays crucial importance for practical application to clarify the coupled nonlinear effects of multi-parameter uncertainty from temperature-dependent material properties, electrical and thermal working conditions, configuration, and geometry size on the performance of thermoelectric generator (TEG). This paper develops a comprehensive tool for optimal geometry design of the multi-stage TEG and identifies the synergistic impacts of the multi-parameter uncertainty on its optimal performance. A novel balanced impedance matching model is established for the first time to balance the optimal output power and conversion efficiency. The developed method is then efficiently integrated with optimization and uncertainty analysis methods. The designed three-stage TEG could achieve better performance due to the optimal working temperature range obtained for each stage, reaching an optimal efficiency of 18.06% under a temperature difference of 500 K. Compared to the single-stage TEG, a remarkable increase of 36.40% for output power and 34.47% for conversion efficiency are achieved for the convective heat transfer conditions, respectively. Uncertainty analysis has indicated that the uncertainty of Seebeck coefficients, leg length ratios, and working temperature conditions have significant impacts on the performance of multi-stage TEG. In contrast, the uncertainty of leg cross-section area ratios and external electrical loading have less effect. The coupled effects of multiple parameters with a total number up to 26 for three-stage TEG are studied in detail. Overall, this work provides a promising comprehensive tool for intensifying TEG performance and clarifying the nonlinear coupled effects of multi-parameter inherent uncertainty.

【 授权许可】

Unknown