熱電發電器（thermoelectric generator）是一種將熱能轉換成電能之設備，具有很大的前景性，熱電發電器之熱源能夠回收廢熱，進而提升燃料之使用效率。本研究針對熱電發電系統，分為兩個部分，第一部分為探討週期性溫度對熱電發電器影響之研究，第二部分為運用基因演算法進行元件幾何形狀之最佳化設計。
第一部分的研究中，操作條件之控制是提高熱電發電器輸出功率的有效方法。本研究之目的在於探討一個數值熱電發電器之輸出功和效率，以及找到使其最佳化的性能之操作條件。熱電發電器在熱面以及冷面的溫度分布近似於正弦函數。溫度振幅在熱端表面、冷端表面、以及不同相位角對熱電發電器的性能影響進行分析。熱電發電器的平均功率和效率能藉由溫度之振盪而明顯增加、但平均吸收熱只有些微影響。增加熱端表面的溫度振幅以及相位角可以有效地提昇熱電發電器之性能。當相位角為0 °時，在冷端表面，小的溫度振幅其性能比大的溫度振幅還要好。當熱電發電器之ZT值從0.736增加至1.8，相位角為180 °之平均效率可增強1.71倍，並且最大平均效率為8.45%。總而言之，相位角為180 °時，在熱端表面，大的溫度振幅是最佳化性能可行的操作。
第二部分之研究目的為探討熱電發電器輸出功和效率藉由使用熱管之廢熱，以及優化其性能，熱電發電器的材料和室溫下之ZT值分別為Bi0.4Sb1.6Te3和1.18。結果顯示，熱端在定熱通量時，較長的元件長度具有更大的輸出功率以及效率；然而熱端在定溫時，較短的元件長度具有更大的輸出功率。透過多目標基因演算法（MOGA）設計熱電發電器之幾何結構，以最大化其效率。當溫差維持在40 ºC時，經過優化後之熱電發電器和原來之做比較，其輸出功率和效率提升約51.9 % 和5.4 %。一旦使用阻抗匹配，即內部電阻等於外部負載電阻，其輸出功率可以進一步提升約3.85-4.40％。當熱端之熱通量固定在20,000 W m-2,且冷熱端之溫差為40 ºC時，一對TEG元件之輸出功和效率可以分別達到7.99 mW和9.52 %。這些結果遠高於其他之研究報告。因此，可以得出結論，MOGA是設計熱電發電器之幾何形狀以便最大化其性能的強大工具。

The thermoelectric generator (TEG) is a promising device to convert heat into electricity. The heat sources TEG recover waste heat to make a more efficient usage of fuels. This study of a thermoelectric generator system is divided into two parts. The first part explores effect of periodic temperature on a module's performance; the second part is optimal design of element geometry by genetic algorithm.
In the first part, operation control is an effective way to improve the output power of TEGs. The present study is intended to numerically investigate the power output and efficiency of a TEG and find the operating conditions for maximizing its performance. The temperature distributions at the hot side and cold side surfaces of the TEG are approximated by sinusoidal functions. The influences of the temperature amplitudes at the hot side surface and the cold side surface, the phase angle, and the figure-of-merit (ZT) on the performance of the TEG are analyzed. The predictions indicate that the mean output power and efficiency of the TEG are significantly enhanced by the temperature oscillation, whereas the mean absorbed heat by the TEG is slightly influenced. An increase in the temperature amplitude of the hot side surface and the phase angle can effectively improve the performance. For the phase angle of 0 °, a smaller temperature amplitude at the cold side surface renders the better performance compared to that with a larger amplitude. When the ZT value increases from 0.736 to 1.8, the mean efficiency at the phase angle of 180 ° is amplified by a factor of 1.72, and the maximum mean efficiency is 8.45 %. In summary, a larger temperature amplitude at the hot side surface with the phase angle of 180 ° is a feasible operation for maximizing the performance.
The purpose of second part is to investigate the output power and efficiency of a TEG system using waste heat from heat pipes, and then optimize its performance. The TEG material is Bi0.4Sb1.6Te3 and the figure-of-merit (ZT) is 1.18 at room temperature. The predictions indicate that a longer length of the elements has greater power output and efficiency based on a fixed heat flux on the hot side surface, whereas a shorter length has greater output power based on a fixed temperature difference. The geometry of the TEG is designed through a multi-objective genetic algorithm (MOGA) to maximize its efficiency. When the temperature difference is fixed at 40 ºC, the output power and efficiency of the TEG with optimization is increased by about 51.9% and 5.4%, compared to the TEG without optimization. Once the impedance matching, namely, the internal resistance is equal to the external load resistance, is used, the output power can be further enhanced by about 3.85-4.40%. When the heat flux is fixed at 20,000 Wm-2 along with the temperature difference of 40 ºC, the output power and efficiency of a pair of elements can be increased to 7.99 mW and 9.52%, respectively. These results are much higher than those reported in other studies. Accordingly, it is concluded that the MOGA is a powerful tool to design the geometry of a TEG for maximizing its performance.

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