热电发电机多材料拓扑优化

Xiaoqiang Xu, Yongjia Wu, L. Zuo, Shikui Chen
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引用次数: 1

摘要

超过50%的来自发电厂、汽车、炼油、钢铁或玻璃制造过程的能量作为废热释放到大气中。作为应对日益严重的能源危机的一种尝试,利用塞贝克现象将废热转化为电能的固态热电发电机(TEG)越来越受欢迎。由于热电材料的性能指标与温度有关,仅使用一种热电材料在较宽的温度范围内实现热电转换的高效率是不可行的。为了解决这一挑战,本文提出了一种基于拓扑优化的方法来优化由多种材料组成的功能梯度teg的布局。优化问题的目标是使输出功率和转换效率最大化。该方法采用固体各向同性材料惩罚法(SIMP)实现。该方法通过将不同热电材料分配到其最佳工作温度区间,可以最大限度地发挥不同热电材料的潜力。P型和n型电导体均采用两种不同的实用热电材料(P型分别为Bi2Te3和PbTe, n型分别为Bi2Te3和CoSb3)进行优化分布,在Tc = 25℃和Th = 400℃温度范围内,屈服转换效率均在12.5%左右。然而在2.5D计算模拟中,转换效率明显下降。这可能是由于外部负载和内部TEG电阻的不匹配以及本文所讨论的拓扑优化结果中的灰色区域。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multimaterial Topology Optimization of Thermoelectric Generators
Over 50% of the energy from power plants, vehicles, oil refining, and steel or glass making process is released to the atmosphere as waste heat. As an attempt to deal with the growing energy crisis, the solid-state thermoelectric generator (TEG), which converts the waste heat into electricity using Seebeck phenomenon, has gained increasing popularity. Since the figures of merit of the thermoelectric materials are temperature dependent, it is not feasible to achieve high efficiency of the thermoelectric conversion using only one single thermoelectric material in a wide temperature range. To address this challenge, this paper proposes a method based on topology optimization to optimize the layouts of functional graded TEGs consisting of multiple materials. The objective of the optimization problem is to maximize the output power and conversion efficiency as well. The proposed method is implemented using the Solid Isotropic Material with Penalization (SIMP) method. The proposed method can make the most of the potential of different thermoelectric materials by distributing each material into its optimal working temperature interval. Instead of dummy materials, both the P and N-type electric conductors are optimally distributed with two different practical thermoelectric materials, namely Bi2Te3 & PbTe for P-type, and Bi2Te3 & CoSb3 for N-type respectively, with the yielding conversion efficiency around 12.5% in the temperature range Tc = 25°C and Th = 400°C. In the 2.5D computational simulation, however, the conversion efficiency shows a significant drop. This could be attributed to the mismatch of the external load and internal TEG resistance as well as the grey region from the topology optimization results as discussed in this paper.
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