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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 陽毅平(Yee-Pien Yang) | |
dc.contributor.author | Ying-Che Shih | en |
dc.contributor.author | 石穎哲 | zh_TW |
dc.date.accessioned | 2021-06-16T16:32:29Z | - |
dc.date.available | 2015-01-16 | |
dc.date.copyright | 2013-01-16 | |
dc.date.issued | 2012 | |
dc.date.submitted | 2012-12-05 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63281 | - |
dc.description.abstract | 複合動力電動車的動力鏈由多顆特性不同的馬達所組成,這些馬達存在不同的高效率區間。本研究利用粒子群最佳化法發展複合動力電動車的節能動力分配即時策略,使車輛於不同行車模式下皆能透過動力分配,操作這些馬達於高效率區間中,以提升整體行車效率,並透過Hardware-In-the-Loop(HIL)的實驗平台驗證本策略的節能性與即時性。接著針對複合動力電動車進行動態規劃分析,以反向式的計算獲得最佳化的動力分配情形,同時也分析使用單動力的傳統電動車於相同行車模式下的行駛效率。透過以上模擬結果的比較,本策略於諸多性能皆有突出的表現。
此外,本研究也針對複合動力電動車的馬達建立模型,此模型以有限元素分析的結果作為馬達參數的資料,並以考慮磁通飽和的增量電感做為馬達的電感資料。因增量電感隨不同電流下的數值不同,使得建立電感資料庫的過程繁雜且耗時。本研究也提出增量電感簡化公式,將繁雜的電感資料得以簡化,以加速有限元素分析的時間。最後透過馬達實測結果的比較,分別從相電流波形、馬達力矩-轉速曲線與馬達效率圖驗證本馬達模型的準確性。 | zh_TW |
dc.description.abstract | The power train of the multi-powered electric vehicle consists of three motors that have different characteristics. This study aims to develop a real-time driving strategy to improve energy economy by particle swarm optimization. It aims to ascertain an optimal power distribution to operate these motors in a high efficiency area and improve driving efficiency. The economy and real-time performance were proven by hardware-in-the-loop platform. Then, we obtained the globe optimal power distribution based on dynamic programming, and we also analyzed the driving efficiency of a traditional electric vehicle to compare the benefits of our real-time strategy.
This study also developed useful models for three different traction motors used in a multi-powered electric vehicle. The motor parameters in these models used the results of finite element analysis. The incremental inductance that considers the flux saturation was used in these models. Since the process of incremental inductance analysis is complicated and time-consuming, we proposed simplified incremental inductance formulas to reduce the time in finite element analysis. Finally, we compared the phase current, torque-speed curve and efficiency map to verify the model. | en |
dc.description.provenance | Made available in DSpace on 2021-06-16T16:32:29Z (GMT). No. of bitstreams: 1 ntu-101-R99522835-1.pdf: 25758175 bytes, checksum: 3a44ea27c8842cdf3d7d10e07bec4e23 (MD5) Previous issue date: 2012 | en |
dc.description.tableofcontents | 誌謝 IV
中文摘要 VI Abstract VIII 目錄 X 圖目錄 XII 表目錄 XX 符號表 XXII 第1章 緒論 1 1.1研究動機與目的 2 1.2文獻回顧 4 1.3章節摘要 12 第2章 複合動力電動車系統模型 15 2.1複合動力電動車架構 16 2.2馬達 19 2.3傳動齒輪箱 20 2.4輪胎模型 21 2.5車體模型 24 2.6電池模型 27 第3章 永磁無刷馬達運作原理 29 3.1永磁無刷馬達簡介 30 3.2方波驅動原理 36 3.3空間向量弦波驅動原理 41 第4章 永磁無刷馬達建模與驗證 51 4.1前言 52 4.2馬達系統方程式 56 4.3馬達驅動模型 63 4.4有限元素法獲得馬達參數 80 4.5 永磁無刷馬達完整模型 101 4.6前輪50kW馬達模擬與驗證 103 4.7後輪28kW馬達模擬 114 4.8討論 117 第5章 行車動態規劃分析 119 5.1動態規劃法 120 5.2行車動態規劃分析 126 5.2.4動態規劃流程 135 5.3模擬結果 144 5.4傳統電動車模擬 154 5.5順向模擬驗證 169 第6章 節能動力分配即時策略 175 6.1粒子群最佳化法(PSO) 176 6.2 節能動力分配即時策略 179 第7章 實驗與綜合比較 196 7.1 HIL實驗平台 197 7.2 HIL運算流程 198 7.3 HIL實驗結果 200 7.4行車效率綜合比較 213 第8章 結論 221 8.1結論 222 8.2未來展望 223 參考文獻資料 225 作者簡介 233 | |
dc.language.iso | zh-TW | |
dc.title | 應用粒子群最佳化之複合動力電動車節能動力分配即時策略 | zh_TW |
dc.title | Energy Economy Real-time Driving Strategy for an Electric ehicle with Multiple Traction Motors by Particle Swarm ptimization | en |
dc.type | Thesis | |
dc.date.schoolyear | 101-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李綱(Kang Li),彭明燦(Ming-Tsan Peng) | |
dc.subject.keyword | 粒子群最佳化法,動態規劃,永磁同步馬達,增量電感,電動車, | zh_TW |
dc.subject.keyword | Particle Swarm Optimization,Dynamic Programming,permanent magnet synchronous motor,incremental inductance,electric vehicle, | en |
dc.relation.page | 233 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2012-12-05 | |
dc.contributor.author-college | 工學院 | zh_TW |
dc.contributor.author-dept | 機械工程學研究所 | zh_TW |
顯示於系所單位: | 機械工程學系 |
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