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研究生: 林芮慶
Lin, Ruei-Cing
論文名稱: 基於交叉耦合電壓下降法之最佳化鋰電-超級電容混合電能管理系統
Optimal Battery-Supercapacitor Hybrid Power System Based on Cross-coupled Droop Control Method
指導教授: 陳瑄易
Chen, Syuan-Yi
學位類別: 碩士
Master
系所名稱: 電機工程學系
Department of Electrical Engineering
論文出版年: 2020
畢業學年度: 108
語文別: 中文
論文頁數: 159
中文關鍵詞: 生物地理演算法最小等效能耗法規則庫混合電力系統電壓下降法交叉耦合控制直流-直流轉換器
英文關鍵詞: biogeographic-based optimization, equivalent consumption minimization strategy, hybrid power system, rule-based control, droop control method, cross-coupled control, DC-DC converter
DOI URL: http://doi.org/10.6345/NTNU202001231
論文種類: 學術論文
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  • 第一章 緒論 1 1.1 研究背景與動機 1 1.2 文獻探討 3 1.3 研究目的 8 1.4 研究架構 9 第二章 DC-DC轉換器系統介紹 11 2.1 DC-DC升/降壓轉換器 11 2.1.1 DC-DC轉換器降壓模式 11 2.1.2 DC-DC轉換器升壓模式 13 2.2 雙向DC-DC轉換器模式分析 16 2.3 多模組DC-DC轉換器控制架構 19 2.3.1 主動均流法 20 2.3.2 電壓下降法 25 2.3.3 改良型電壓下降法 30 2.3.4 交叉耦合電壓下降法 33 第三章 交叉耦合電壓下降法之PSIM模擬 37 3.1 PSIM軟體介紹 37 3.2 PID控制系統 38 3.3 電壓下降法之PSIM軟體建模 40 3.4 改良型電壓下降法之PSIM軟體建模 45 3.5 交叉耦合電壓下降法之PSIM軟體建模模 50 3.6 自動主僕法應用於內迴路調節架構之PSIM建模 55 3.7 模擬結果比較 60 第四章 交叉耦合電壓下降法之實驗介紹與結果討論 63 4.1 實驗平台介紹 63 4.1.1 系統硬體介紹 64 4.2 交叉耦合電壓下降法之實驗結果 71 4.3 實驗結果比較 76 第五章 混合電能系統之最佳化能量管理策略 78 5.1 鋰電池模組[36][45] 78 5.2 超級電容模組[46] 80 5.3 基本規則庫控制策略 82 5.4 最小等效能耗法控制策略 84 5.5 生物地理演算法 88 5.5.1 生物地理學之數學模型 89 5.5.2 生物地理演算法流程[29] 92 5.5.3 生物地理演算法之能量管理控制策略 95 5.6 改良型生物地理演算法 97 5.6.1 改良型生物地理演算法之能量管理控制策略 100 第六章 最佳化能量管理策略之Matlab模擬 103 6.1 車輛動態模型 103 6.1.1 行車型態 105 6.2 基本規則庫控制策略之模擬結果 108 6.3 最小等效能耗控制策略之模擬結果 111 6.4 生物地理演算法控制策略之模擬結果 113 6.5 改良型生物地理演算法控制策略之模擬結果 115 6.6 模擬結果之能耗比較 117 第七章 實驗平台介紹與結果討論 121 7.1 實驗平台說明 121 7.2 WMTC行車型態實驗結果 124 7.2.1 基本規則庫控制策略之實驗結果 124 7.2.2 最小等效能耗策略之實驗結果 127 7.2.3 生物地理演算法策略之實驗結果 129 7.2.4 改良型生物地理演算法之實驗結果 132 7.3 NEDC行車型態實驗結果 135 7.3.1 基本規則庫控制策略之實驗結果 135 7.3.2 最小等效能耗策略之實驗結果 138 7.3.3 生物地理演算法策略之實驗結果 141 7.3.4 改良型生物地理演算法之實驗結果 144 7.4 實驗結果之能耗比較 147 第八章 結論與未來展望 151 8.1 結論 151 8.2 未來展望 152 參考文獻 153

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