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研究生: 許繼嘉
XU, Ji-Jia
論文名稱: 混合動力平台機電整合系統測試驗證與最佳化能量管理
Experimental Verification for a Hybrid Powertrain Platform with Optimal Energy Management Control System
指導教授: 洪翊軒
Hung, Yi-Hsuan
學位類別: 碩士
Master
系所名稱: 工業教育學系
Department of Industrial Education
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 99
中文關鍵詞: 人工蜂群演算法基本 規則庫混合動力綠色能源機電整合
英文關鍵詞: Artificial bee colony algorithm, Rule based, Hybrid powertrain, Green energy, Mechatronics
DOI URL: http://doi.org/10.6345/NTNU202000903
論文種類: 學術論文
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  • 本研究中依過往的混合動力平台強化一種七模式的車輛混合動力平台機電整合系統,用來評估各種混合動力組合的性能測試。平台設計方面選擇了三種動力源來提供混合動力,第一個動力源是1.5kW輪轂電動馬達,第二個動力源是125c.c.汽油引擎,第三個動力源是空氣引擎,利用三電磁離合器使動力源可獨立運作或進行混合動力輸出。電子磁粉制動器模擬道路負載。Matlab/Simulink軟體接收測量的信號並執行控制命令,通過三個可控離合器的開與關狀態控制,可以執行三種單動力模式、三種雙動力模式和一種三動力模式共七種操作模式。運用混合動力平台測得引擎/馬達效率並於Matlab/Simulink軟體建置雙動力混合動力系統實驗性能分析,選定歐盟規範之ECE40 (Four Cycles)行車型態進行測試,並以人工蜂群演算法搜尋雙動力源之最佳動力分配比例,達到最小等效油耗。模擬最佳化演算法並與規則庫控制相比節能效益。研究結果顯示:第一此平台可以進行七種動力模式測試,證明了混合動力組合的高度靈活性。將來可以應用於其他動力源;第二相較於規則庫控制,仿生最佳化演算法具有較佳的節能效益,採用人工蜂群演算法於雙動力引擎/馬達系統中之能耗改善為28.5%。

    This study developed a mechatronics platform for a seven-mode vehicle-oriented powertrain system. It is used for flexibly arranging various power or energy sources to be combined for various hybrid powertrains. In this study, three power sources were chosen for providing hybrid power. The first source is a 1.5kW hub motor, the second one is a 125 c.c. spark ignition engine, and the third source is an air engine, With the help of e-clutches, different power sources can be combined into hybrid powertrain or separated from it. A magnetic powder brake emulates the road load. Matlab/Simulink package receives the measured signals and sends the control commands to actuators. Through the on and off state control of three controllable e-clutches, three single-source modes, three dual-source modes, and one three-source mode, a total seven-mode can be conducted. Use the hybrid platform to measure engine/motor efficiency and Matlab/Simulink software builds a dual-power hybrid system experimental performance analysis, We selected the EU-standard ECE40 (four cycles) model for testing, and then used artificial bee colony algorithm (ABC) to search for the best power distribution ratio of the dual engine/motor power source, to reach the minimum equivalent fuel consumption. Simulated optimization algorithm was compared with rule-based for the evaluation of energy-saving benefits. The research results show that : first, the platform can test seven power modes, it proving the high flexibility of the hybrid combination. In the future, it can be applied to other power sources. Second, compared with rule-based control, the bionic optimization algorithm has better energy-saving benefits. And use with ABC the energy consumption compared with that of the rule-based control can be improved by 28.5%.

    摘 要 i Abstract ii 誌 謝 iv 目 次 v 表 次 ix 圖 次 x 第一章 緒論 1 1.1 前言 1 1.2 研究動機 2 1.3 研究目的 3 1.4 研究方法 4 1.5 文獻回顧 6 1.6 論文架構 10 第二章 混合動力平台與模擬系統架構 11 2.1 混合動力平台架構 11 2.2 電動馬達性能架構 13 2.3 汽油引擎性能架構 15 2.4 空氣引擎性能架構 16 2.5 混合動力平台整體架構 18 2.6 混合動力平台控制程式 22 2.7 模擬系統架構 26 2.8 行車型態模塊 29 2.9 路面負載模塊 29 2.10 內燃引擎整合CVT模塊 30 2.11 電動馬達模塊 32 2.12 鋰電池模塊 33 第三章 七模式混合動力平台操作與控制 35 3.1混合動力平台控制策略 35 3.2單動力源模式(C1^3) 38 3.2.1電動馬達模式 38 3.2.2汽油引擎模式 40 3.2.3空氣引擎模式 41 3.3雙動力源模式(C2^3) 43 3.3.1電動馬達與汽油引擎模式 43 3.3.2汽油引擎與空氣引擎模式 44 3.3.3電動馬達與空氣引擎模式 45 3.4三動力源模式(C3^3) 46 3.5基本性能測試 47 3.6基本規則庫控制策略 47 3.7人工蜂群演算法控制策略 49 3.7.1人工蜂群演算法步驟介紹 49 3.7.2人工蜂群演算法參數設置 52 3.7.3人工蜂群演算法控制變數與動力分配比關係 53 3.7.4人工蜂群演算法流程介紹 54 第四章 測試結果與討論 57 4.1電動馬達與汽油引擎試驗 57 4.1.1電動馬達及汽油引擎速度之關係 57 4.1.2電動馬達及汽油引擎扭力之關係 58 4.1.3電動馬達及汽油引擎輸入功率之關係 59 4.1.4電動馬達及汽油引擎輸出功率之關係 60 4.1.5電動馬達及汽油引擎效率之關係 61 4.2汽油引擎與空氣引擎試驗 62 4.2.1汽油引擎及空氣引擎速度之關係 62 4.2.2汽油引擎及空氣引擎扭力之關係 63 4.2.3汽油引擎及空氣引擎輸入功率之關係 63 4.2.4汽油引擎及空氣引擎輸出功率之關係 64 4.2.5汽油引擎及空氣引擎效率之關係 65 4.3電動馬達與空氣引擎試驗 66 4.3.1電動馬達及空氣引擎速度之關係 66 4.3.2電動馬達及空氣引擎扭力之關係 67 4.3.3電動馬達及空氣引擎輸入功率之關係 68 4.3.4電動馬達及空氣引擎輸出功率之關係 69 4.3.5電動馬達及空氣引擎效率之關係 70 4.4電動馬達、汽油引擎與空氣引擎試驗 71 4.4.1電動馬達、汽油引擎與空氣引擎速度之關係 71 4.4.2電動馬達、汽油引擎與空氣引擎扭力之關係 73 4.4.3電動馬達、汽油引擎與空氣引擎輸入功率之關係 74 4.4.4電動馬達、汽油引擎與空氣引擎輸出功率之關係 75 4.4.5電動馬達、汽油引擎與空氣引擎效率之關係 76 4.5基本性能結果 77 4.6基本規則庫與人工蜂群演算法控制策略試驗 79 4.6.1基本規則庫模式切換 79 4.6.2基本規則庫控制馬達動力輸入結果 80 4.6.3基本規則庫控制動力輸出結果 81 4.6.4基本規則庫控制能量消耗結果 83 4.6.5人工蜂群演算法控制動力分配 84 4.6.6人工蜂群演算法控制馬達動力輸入結果 85 4.6.7人工蜂群演算法控制動力輸出結果 87 4.6.8人工蜂群演算法控制能量消耗結果 88 4.7能耗比較結果 90 第五章 結論與未來建議 91 5.1結論 91 5.2未來建議 92 參考文獻 93 符號彙整 97

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