| 研究生: |
黃子軒 Huang, Zi-xuan |
|---|---|
| 論文名稱: |
利用反應曲面法配合基因演算法分析陣列式高功率LED構裝散熱之最佳設計 Optimal Design of Dissipation for the Array Power LED by the RSM with Genetic Algorithm |
| 指導教授: |
陳榮盛
Chen, Rong-cheng |
| 學位類別: |
碩士 Master |
| 系所名稱: |
工學院 - 工程科學系 Department of Engineering Science |
| 論文出版年: | 2010 |
| 畢業學年度: | 98 |
| 語文別: | 中文 |
| 論文頁數: | 158 |
| 中文關鍵詞: | 基因演算法 、反應曲面法 、陣列式LED 、部份因子設計法 |
| 外文關鍵詞: | Array LED, Factorial design method, Response surface method, Genetic algorithm |
| 相關次數: | 點閱:97 下載:3 |
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隨著LED 發光效能之提升,LED已經漸漸被發展成具有高效能、高可靠度、壽命長、多元目的與消耗功率低等多項功能。因此使得陣列式LED 逐漸被廣泛應用於人類生活中。
本研究利用ANSYS 有限元素分析軟體對陣列式LED進行熱行為分析。其中陣列式LED之建模係由四顆相同尺寸之LED金屬芯基板與底座散熱塊結合而成。經Flotran熱流分析求出空氣自然對流係數,而對流值可藉由疊代法加以確認,因為對流值被設定為ANSYS熱分析之邊界條件以求出溫度分佈,並使晶片接合溫度及底座散熱塊溫度與產品C1-121的要求相符。
在進行晶片接合溫度最佳化之前,先以部份因子設計法篩選出顯著的控制因子,再分別以雙反應曲面法與混合反應曲面法建構出迴歸模型,並以反應曲面結合基因演算法進行參數最佳化設計,及討論雙反應曲面法與混合反應曲面法獲得之結果。隨後,以混合反應曲面法探討各參數間的交互作用對晶片接合溫度的影響。最後,研究結果發現金屬芯基板熱傳導係數與底座散熱塊高度對晶片接合溫度的影響最大。其次晶片尺寸與晶片黏著層熱傳導係數之交互作用對晶片接合溫度的影響最為明顯。
In accordance with the improvement in its luminous efficiency, light emitting diode(LED) has been gradually developed with functions of high power, good reliability, long life, multiple purposes and low power consumption.As a result, the array LED has been broadly applied in human livings nowadays.
This study applies the ANSYS finite element analysis software to analyze the thermal behaviors of the array LED. The array LED is modeled by 4 same-size LEDs with metal core substrate on a heat-sink. The air natural convection coefficient is obtained by the Flotran heat flow analysis. Thus, this value of the convection can be verified through the iterative method since such convective value is set as the boundary conditions of the ANSYS thermal analysis to obtain the temperature distribution in which the chip junction temperature and heat-sink temperature are conformed the requirement of the C2-121 product.
Prior to the process of the optimal design on the chip junction temperature, the most significant parameters are chosen by the fractional factorial design method. The regressive models are set up by the double response surface method and the mixed response surface method respectively. Furthermore the genetic algorithm combined with the response surface is applied to obtained the optimal design parameters, then the results obtained by both two methods are discussed. Afterwards, a mixed response surface method is applied to analyze the interactive effects among various parameters on the chip junction temperature. Finally it is found that the metal core substrate thermal conductivity and the heat-sink height are the most significant factors. Besides, the interactive effects between the size of chip and the thermal conductivity of the chip adhesion layer are the most obvious effects on the chip junction temperature.
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