臺灣博碩士論文加值系統

近年來，全球暖化的危害程度與日俱增，許多國家都意識到替代能源的重要性，所以各國開始強調環保和無汙染的電力驅動交通工具，像是電動汽車、電動機車、電動自行車等等，其中電動輔助自行車為老少咸宜的休閒活動，不只能作為代步工具，還能達到運動的目的，然而電動輔助自行車如何依照不同路況及不同騎乘者習慣產生對應的輔助力成了重要的議題。
一般的商業電動輔助自行車採用傳統的固定式輔助力或比例式輔助力，但此兩種簡易的方法都無法在面臨不同路況做及時的調整。而現有的智能控制方法中，傳統的模糊控制器經由專家經驗所設計的模糊參數，並不會因為騎乘習慣的差異而自動調整至符合該騎乘者的模糊參數，所以並不適用於不同騎乘者的騎乘習慣，進而降低騎乘者的騎乘品質。
本文藉由力矩感測器及輪速感測器所得到的行車資訊去設計使用者自適應模糊控制器，除了能根據不同的路況，適時給予騎乘者適當的電動輔助力之外，還能根據不同騎乘者的騎乘習慣調整模糊參數，以達到滿足騎乘品質的需求，包含舒適性及安全性這兩項指標，使得電動輔助自行車可以維持穩定的速度及加速度行駛。

In recent years, the degree of damage due to global warming has grown with each passing day. Many countries have realized the importance of alternative energy sources. Therefore, many countries have begun to emphasize on environmental protection and less-polluting electric drive vehicles, such as: electric vehicles, electric motor, and electric bikes. Wherein, riding the electric-assist bikes is a recreational activity for all ages. Electric-assist bikes not only can be travel tools, but also can achieve the sport purpose. However, how to generate corresponding assisted force has become an important issue depending on different road conditions and different rider’s habits.
General commercial electric-assist bikes use traditional constant controller or proportional controller to generate the motor power. But these two simple methods cannot adjust assisted power timely for different road conditions. In the existing intelligent control methods, due to traditional fuzzy controller designs the fuzzy parameter via expert experience, it cant adjust automatically to match the riders fuzzy parameter. This result is not suitable for different riders riding habit. It will reduce the riders quality of riding.
In this paper, we use torque senor and wheel speed sensor to obtain the riding information that can be used to design the user-adaptive fuzzy logic controller. Our designed user-adaptive fuzzy logic controller can provide timely efficient assisted power on different road conditions. Moreover, it could adjust fuzzy logic control parameter based on different rider’s riding habit to achieve the quality-of-riding requirement, i.e., safety and comfort. The proposed system allows the electric-assist bikes to maintain the stable bike velocity and acceleration.

摘　要 i
ABSTRACT ii
誌 謝 iv
目錄 v
表目錄 viii
圖目錄 ix
第一章 緒論 1
1.1研究背景 1
1.2研究動機與目的 1
1.3文獻回顧 2
1.3.1傳統助力控制器 2
1.3.2模糊助力控制器 3
1.3.3強化學習助力控制器 4
1.4問題陳述 6
1.5研究方法 6
1.6研究貢獻 6
1.7論文架構 7
第二章 電動輔助自行車相關系統 8
2.1動力系統 9
2.2儲能系統 10
2.3傳動系統 12
2.3.1騎乘環境阻力 12
2.3.2傳動系統 15
第三章 本文提出之使用者自適應模糊控制器 18
3.1模糊控制理論 18
3.1.1模糊理論介紹 18
3.1.2模糊控制系統設計 18
3.1.2.1 模糊化 19
3.1.2.2 知識庫 19
3.1.2.3 推論引擎 21
3.1.2.4 解模糊化 22
3.2 本文提出於助力控制系統之使用者自適應模糊控制器 23
3.2.1模糊推論應用於助力控制系統 25
3.2.1.1 輸入歸屬函數設計 25
3.2.1.2 模糊規則庫設計 27
3.2.1.3 輸出歸屬函數設計 28
3.2.2使用者自適應糢糊控制器 28
第四章 系統架構設計與實現 31
4.1硬體部分 31
4.1.1 BeagleBone Black單晶片 31
4.1.2助力馬達 32
4.1.3力矩感測器 33
4.1.4輪速感測器 35
4.2軟體部分 35
4.2.1 Matlab系統輸出模擬 35
4.2.2 BeagleBone Black開發環境 36
4.2.3網頁監控介面開發環境 37
4.3電動輔助自行車系統架構與實現 38
4.3.1電動輔助自行車系統實現 39
4.3.2網頁監控介面實現 40
第五章 系統模擬與實驗結果 42
5.1騎乘品質評估準則 42
5.2純模糊控制器之模擬結果 43
5.2.1模擬場景設置 43
5.2.2比較方法的設計 45
5.2.3 70kg的騎乘者之模擬結果 47
5.3使用者自適應模糊控制器之模擬結果 56
5.3.1模擬場景設置 56
5.3.2比較方法的設計 56
5.3.3不同騎乘者習慣之模擬結果 57
5.3.4模擬結果討論 63
5.4道路實測結果 65
5.4.1道路實測場景 65
5.4.2助力控制器之模擬結果 68
5.4.3模擬與實作差異分析 70
第六章 結論與未來工作 73
6.1結論 73
6.2未來工作 74
參考文獻 76

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