臺灣博碩士論文加值系統

本論文以電動輔助自行車之車架作為分析目標，根據歐盟EN15194電動輔助自行車標準進行落錘試驗與前倒試驗之規範要求，選擇車架上、下管的第一段與第五段之長度與厚度作為分析的控制因子，使用ANSYS/LS-DYNA有限元素分析軟體模擬，分析求得車架前叉的最大變形量，透過均勻實驗設計與規劃一系列的模擬實驗，求出最終的改善方案，透過均勻實驗設計可以看出各單一目標的最大改善率，應用Kriging插值法建立數學代理模型，以車架前叉最大變形量作為目標函數，透過基因演算法對子目標求得最佳解後，利用熵權法求得合成目標函數找出最佳的權重值，利用灰關聯法將多目標整合成單目標，並利用基因演算法求出最佳解，最後求得電動輔助自行車車架之最佳設計參數。
研究結果顯示，經由均勻實驗設計與最佳化設計，並使用基因演算法所求得之車架尺寸與原始車架設計值相互比較，落錘試驗的前叉最大變形量改善3.47%，而前倒試驗的前叉最大變形量改善4.18%，試驗的兩個目標同時改善，達到多目標改善設計效果，並建立了一套有效的最佳化設計流程。

The frame of electric assisted bicycle is taken as the analysis target in this paper. The length and thickness of the first section and the fifth section of the upper and lower tubes of the frame are selected as the control factors for the analysis according to the requirements of the drop-mass impact and the fall-frame impact test of the European standard EN 15194 for electric assisted bicycles. The finite element analysis software ANSYS/LS-DYNA is used to simulate and analyze the permanent deformation of the front fork of the frame. Through uniform experimental design and planning of a series of simulation experiments, the final improvement scheme is obtained. Based on uniform design, the maximum improvement rate of each single target can be seen, and Kriging interpolation method is used to establish a mathematical agent model. Taking the permanent deformation of the front fork of the frame as the objective function, the optimal solution of the sub-objective is obtained by genetic algorithm, and the synthetic objective function is obtained by entropy method to find the best weight ratio. The grey relational method is used to integrate multiple objectives into a single objective, and genetic algorithm is used to find the best solution again. Finally, the best design parameters of the frame of electric assisted bicycle are obtained.
The results show that the permanent deformation of front fork is improved by 3.47% in drop-mass impact test by comparing the frame size obtained by uniform design and optimal design and using genetic algorithm with the original frame design value. And the permanent deformation of the front fork in the fall-frame impact test is improved by 4.18%. The two objectives of the experiment are improved simultaneously, and the multi-objective improvement design effect is achieved, and an effective optimization design process is established.

摘要 I
ABSTRACT II
致謝 IV
表目錄 VIII
圖目錄 IX
符號說明 XI
第一章 緒論 1
1-1 簡介 1
1-2 文獻回顧 2
1-2-1電動輔助自行車相關文獻 2
1-2-2 均勻實驗與最佳化演算法的應用 3
1-2-3 Kriging空間插值法的應用 4
1-3 研究動機、目的及方向 5
1-4 論文結構 8
第二章 有限元素分析 10
2-1 有限元素法理論簡介 10
2-2 有限元素法分析步驟 11
2-3 ANSYS-LS-DYNA簡介 12
2-4 ANSYS-LS-DYNA分析流程 13
2-5 車架試驗模擬分析 15
2-5-1 模型建立 15
2-5-2 元素選擇 16
2-5-3 材料選擇 17
2-5-4 接觸問題設定 19
2-5-5 落錘試驗法規介紹 21
2-5-6 前倒試驗法規介紹 23
2-5-7 質塊模型建立 24
2-5-8 邊界條件設定 29
2-5-9 網格設定與收斂性分析 30
2-5-10 動態模擬分析結果 33
第三章 研究方法 36
3-1 均勻實驗設計法簡介 37
3-2 均勻設計表應用 38
3-3 Kriging空間插值法 41
3-4 熵值權重法原理 44
3-5 灰關聯分析 46
3-6 基因演算法 50
第四章 最佳化設計與分析 51
4-1 參數設計 51
4-2 均勻設計表選用 53
4-3 均勻實驗設計結果 58
4-4 建立Kriging模型 58
4-5 多目標規劃 60
4-6 最佳化設計與分析 61
4-7 最佳化設計結果 68
第五章 結論 69
5-1 結論 69
5-2 未來展望 70
參考文獻 71

[1]NSB (National Standards Boards), 「Electrically Powered Assist Cycles, EN 15194」, April. 2009.
[2]楊智淵(2012)，電動自行車車架振動分析。
[3]王怡傑(2017)，應用騎乘姿勢最佳化與有限元素分析於電動輔助自行車車架設計開發之研究。
[4]宋宜駿(2005)，複材自行車架重新設計與力學分析。
[5] 蔡明蒼(2015) ，公路自行車車架落錘測試模擬分析與多目標最佳化設計。
[6]楊百曜(2007)，碳纖維自行車前叉之剛性與強度分析。
[7]Cahyono, S. I., Anwar, M., Diharjo, K., Triyono, T., Hapid, A., & Kaleg, S. (2017). Finite element analysis of electric bicycle frame geometries. AIP Conference Proceedings.
[8]Lessard, L. B., Nemes, J. A., & Lizotte, P. L. (1995). Utilization of FEA in the design of composite bicycle frames. Composites, 26(1), 72-74.
[9]Sorton, A., & Walsh, T. (1994). Bicycle stress level as a tool to evaluate urban and suburban bicycle compatibility. Transportation Research Record, 17-17.
[10]Gorenflo, C., Rios, I., Golab, L., & Keshav, S. (2017). Usage patterns of electric bicycles: an analysis of the WeBike project. Journal of advanced transportation, 2017.
[11]Uludamar, E., Yıldızhan, Ş., Tosun, E., & Aydın, K. (2016). Finite element analysis of electric bike rims coupled with hub motor. Adv Automob Eng, 5(2), 1000142-1000141.
[12]Mesic, E., Masic, A., Muratovic, E., Delic, M., & Hasanbegovic, S. (2021). Structural analysis and optimization of electric bike front drive with bottom bracket electric motor. Advances in Science and Technology. Research Journal, 15(1).
[13]方开泰(1980)，均匀设计——数论方法在试验设计的应用. 应用数学学报, 3(4), 363-372。
[14]Liang, Y.-z., Fang, K.-t., & Xu, Q.-s. (2001). Uniform design and its applications in chemistry and chemical engineering. Chemometrics and Intelligent Laboratory Systems, 58(1), 43-57.
[15]張金廷(1991)，數學幾何模型均勻設計，中國科科學院應用數學所。
[16]Tang, M., Li, J., Chan, L.-Y., & Lin, D. K. (2004). Application of uniform design in the formation of cement mixtures. Quality Engineering, 16(3), 461-474.
[17]買庭勻、謝佳玲、許仲洲(2018)，以均勻實驗設計法及克利金代理模型法探討塑膠射出成型傘齒輪翹曲變形之最佳化設計，高雄師大學報：自然科學與科技類(44) ，43-57。
[18] Shu, X., Gu, C., Xiao, J., & Gao, C. (2008). Centrifugal compressor blade optimization based on uniform design and genetic algorithms. Frontiers of Energy and Power Engineering in China, 2(4), 453-456.
[19]黃哲偉(2017)，均勻實驗設計與多元回歸之函數建模準確度研究。
[20]翁振恭(2004)，使用基因演算法於拓撲最佳化之研究。
[21]Leung, Y.-W., & Wang, Y. (2000). Multiobjective programming using uniform design and genetic algorithm. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 30(3), 293-304.
[22]Trochu, F., Sacepe, N., Volkov, O., & Turenne, S. (1999). Characterization of NiTi shape memory alloys using dual kriging interpolation. Materials Science and Engineering: A, 273, 395-399.
[23]McLean, P., Léger, P., & Tinawi, R. (2006). Post-processing of finite element stress fields using dual kriging based methods for structural analysis of concrete dams. Finite Elements in Analysis and Design, 42(6), 532-546.
[24]Gu, Y., Wang, Q., & Lam, K. (2007). A meshless local Kriging method for large deformation analyses. Computer Methods in Applied Mechanics and Engineering, 196(9-12), 1673-1684.
[25]Afraites, L., Hazart, J., & Schiavone, P. (2009). Application of the Kriging method to the reconstruction of ellipsometric signature. Microelectronic Engineering, 86(4-6), 1033-1035.
[26]施翔智(2021)，多負載條件下的末端效應器絕對定位。
[27]孫偉翔(2016)，公路自行車車架動態應力分析與多目標最佳化設計。
[28]吳勁緯(2020)，一體式車把立管之應力分析與最佳化設計。
[29]Swanson分析系統公司，軟體開發公司，https://www.ansys.com
[30]LSTC (Ansys, Inc.)，軟體開發公司，http://www.lstc.com/products/ls-prepost.
[31]Lee, S.-Y., Lin, S.-M., Sheu, J.-J., & Cheng, Y.-C. (2010). Driving mechanism for the motorized bicycle. In: Google Patents.
[32]Kaufman, J. G. (2000). Introduction to aluminum alloys and tempers. ASM international.
[33]林李旺(2006)“快速精通實驗設計邁向Six Sigma的關鍵方法”，華科技圖書股份有限公司。
[34]曾昭鈞(2005)，均勻設計及其應用:供藥學類、中藥學類專業用，中國醫藥科技出版社。
[35]方开泰(1980)，均匀设计与均匀设计表，科学出版社。
[36]Lophaven, S. N., Nielsen, H. B., & Søndergaard, J. (2002). DACE: a Matlab kriging toolbox (Vol. 2). Citeseer.
[37]徐若倩(2004)，灰關聯分析與 TOPSIS 方法應用於企業經營績效評估之研究。
[38] Clausius, R. (1865). Ueber verschiedene für die Anwendung bequeme Formen der Hauptgleichungen der mechanischen Wärmetheorie: vorgetragen in der naturforsch. Gesellschaft den 24. April 1865. éditeur inconnu.
[39]Işık, A. T. (2017). The decision-making approach based on the combination of entropy and ROV methods for the apple selection problem. European Journal of Interdisciplinary Studies, 3(3), 80-86.
[40]Wu, J., Sun, J., Liang, L., & Zha, Y. (2011). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5), 5162-5165.
[41]He, Y., Guo, H., Jin, M., & Ren, P. (2016). A linguistic entropy weight method and its application in linguistic multi-attribute group decision making. Nonlinear Dynamics, 84(1), 399-404.
[42]Rocha, L. C. S., Paiva, A. P. d., Balestrassi, P. P., Severino, G., & Rotela Junior, P. (2015). Entropy-based weighting for multiobjective optimization: an application on vertical turning. Mathematical Problems in Engineering, 2015.
[43]Vatansever, K., & Akgűl, Y. (2018). Performance evaluation of websites using entropy and grey relational analysis methods: The case of airline companies. Decision Science Letters, 7(2), 119-130.
[44]Yue, C. (2017). Entropy-based weights on decision makers in group decision-making setting with hybrid preference representations. Applied Soft Computing, 60, 737-749.
[45]Zou, Z.-H., Yi, Y., & Sun, J.-N. (2006). Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. Journal of Environmental sciences, 18(5), 1020-1023.
[46]張芷宜(2004)“運用機率限制規劃求解資源及資金供給不確定條件下之重複性工程排程問題
[47]鄧聚龍(1999)，灰色系統理論與應用,” 高立圖書有限公司。
[48]Deng, J. (1982). Control problems of grey systems. Systems and Control Letters, 1, 288–294.
[49]Kuo, Y., Yang, T., & Huang, G.-W. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & industrial engineering, 55(1), 80-93.
[50]Hasani, H., Tabatabaei, S. A., & Amiri, G. (2012). Grey relational analysis to determine the optimum process parameters for open-end spinning. Journal of Engineered Fibers and Fabrics, 7(2), 81-86.
[51]Jegan, T. C., Anand, M. D., & Ravindran, D. (2012). Determination of electro discharge machining parameters in AISI202 stainless steel using grey relational analysis. Procedia engineering, 38, 4005-4012.
[52]Chen, M.-F., & Tzeng, G.-H. (2004). Combining grey relation and TOPSIS concepts for selecting an expatriate host country. Mathematical and computer modelling, 40(13), 1473-1490.
[53]Yuan, C., Yang, Y., & Shui, L. (2013). Generalized grey relation analysis based on approximate true starting points. Journal of Grey System, 25(4), 71.
[54]Leclerc, F., & Potvin, J.-Y. (1997). Genetic algorithms for vehicle dispatching. International Transactions in Operational Research, 4(5-6), 391-400.