کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8072268 | 1521403 | 2018 | 37 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Optimal design of a segmented thermoelectric generator based on three-dimensional numerical simulation and multi-objective genetic algorithm
ترجمه فارسی عنوان
طراحی مطلوب ژنراتور ترموالکتریک جدا شده بر اساس شبیه سازی عددی سه بعدی و الگوریتم ژنتیک چند منظوره
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کلمات کلیدی
ژنراتور ترموالکتریک، شبیه سازی عددی، بهینه سازی چند هدفه، الگوریتم ژنتیک،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی (عمومی)
چکیده انگلیسی
This paper proposes a general method to optimize the structure and load current for a segmented thermoelectric generator (TEG) module, where the bismuth telluride is selected as the cold side material, and the skutterudite is selected as the hot side material, respectively. Two objectives, minimum semiconductor volume Vâ² and maximum output power P, are simultaneously considered to assess the performance of the TEG module. All the simulation models to be optimized by the multi-objective genetic algorithm are established and solved by finite element method, where the Thomson effect, in conjunction with Peltier effect, Joule heating, and Fourier heat conduction are simultaneously considered. In order to achieve the ultimate optimal design, TOPSIS (technique for order preference by similarity to an ideal solution) is employed to determine the best compromise solution. The results of Pareto solutions show that Vâ² varies from 432â¯mm3 to 3868â¯mm3, while P varies from 5.523â¯W to 56.293â¯W, respectively. Meanwhile, optimal design variables are investigated to provide practical guidance for the industrial applications. The mechanism of performance improvement has also been explained in this work by comparing the optimal segmented TEG and the skutterudite TEG.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Energy - Volume 147, 15 March 2018, Pages 1060-1069
Journal: Energy - Volume 147, 15 March 2018, Pages 1060-1069
نویسندگان
Ya Ge, Zhichun Liu, Henan Sun, Wei Liu,