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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 | Chen Cho | en |
dc.contributor.author | 卓震 | zh_TW |
dc.date.accessioned | 2021-06-17T06:00:36Z | - |
dc.date.available | 2024-02-14 | |
dc.date.copyright | 2019-02-14 | |
dc.date.issued | 2019 | |
dc.date.submitted | 2019-02-12 | |
dc.identifier.citation | [1] “旅次的分類-知識百科-三民輔考,” [Online]. Available: http://coltplus.mitsubishi-motors.com.tw/.
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/71431 | - |
dc.description.abstract | 近年來電動車技術逐漸發展成熟,但續航力仍受限於電池容量,若能提供電動車駛者適當的路線規劃,將能夠在相同的電量條件下,提升里程數。電動車隨著動力系統和配置馬達規格的不同,皆有屬於各自最佳效率車速區間,並且能依照此特性尋找最節能路線,然而,傳統的導航應用程式僅提供最快或最短路線選擇,若電動車行駛於傳統規劃路線上,將會造成能量上的浪費。
本論文以實驗室之多動力馬達電動車架構,分析駕駛者旅次行為並提出一套二階段即時節能策略。駕駛者在出發前,啟動第一階段聯網節能路線規劃系統,透過寫入此系統的導航Android應用程式協助駕駛者搜尋節能路線。在車輛行駛途中,啟動第二階段電量平衡策略,提升整車行駛效率。透過此策略之執行,達成搜尋最節能路線、提升續航力和縮小三組電池組間電量差距之三項目的。 聯網節能路線規劃系統使用Google Maps API開發工具取得路線資訊,將此資訊套用至本研究建構之車速曲線模型,預測車輛行駛於該路線之車速曲線圖和每一時刻的車速、加速度值,再由此電動車架構所推導之車輛能耗計算式求得路線能耗。其輕運算量之特性,適合應用在手機應用程式中,不會造成手機電量和運作上的負擔。即時節能動力分配策略與電量平衡策略之整合設計應用粒子群最佳化法,藉由其即時響應與快速收斂的特性迅速分配各馬達的輸出力矩,使馬達能夠操作於整體效率較佳區間。 本研究透過模型迴路(model-in-the-loop, MIL)平台、底盤動力計和上路驗證策略。實驗結果顯示,二階段即時節能策略能夠準確辨別節能路線,相較於單一力矩分配模式,續航力可提升43.2%且能將電量差距維持在±2%。 | zh_TW |
dc.description.abstract | In recent years, electric vehicle technology has been developed maturely. The car endurance is still limited by battery capacity. If a proper route planning can be provided to electric vehicle drivers, driving mileage will be increased under the same capacity. Each electric vehicle, with specificpowertrain and motor characteristics, has an optimal energy-efficient speed range. We can find the most energy-efficient route according to the speed range. However, traditional navigation applications or machines only provide the fastest and shortest route options. If electric vehicles drive on a traditional route, it will result in energy waste.
This research analyzes driver’s trip behavior and proposes a two-stage networked real-time energy-efficient strategy for an electric vehicle driven by multiple motors. First stage is called the networked energy-efficient route planning system. It helps drivers search for an energy-efficient route through the Android navigation APP, implemented in the system. Second stage is called Charging Balancing Strategy. It enhances the vehicle energy performance by torque distribution. Through implementation of the strategy, three goals, which include searching for energy-efficient routes, enhancing endurance, and reducing state of charges between three battery packs, are achieved. Networked real-time energy-efficient strategy uses Google Maps API as a development tool to obtain route information. Thid research then applies this information to the speed curve model to predict the vehicle speed curve, with velocity and acceleration at each moment. Route energy consumption is calculated by vehicles energy consumption equations, derived from the electric vehicle structure. With the advantage of light computational complexity, it’s applicable for mobile phones and without negative impacts on phones’ operation and electricity. The integrated design of the real-time torque distribution and the charge balance strategy applies particle swarm optimization to real-time distribute motor torque with it’s characteristic of quick response and convergence, so that the motor can be operated in better efficiency overall. This strategy is verified by model-in-the-loop platform, chassis dynamometer test, and on-road test. Experimental results show that the strategy can identify the energy-efficient route accurately, save 43.2% energy compared with constant proportion torque distribution, and maintained the charge gap between battery packs at 2% | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T06:00:36Z (GMT). No. of bitstreams: 1 ntu-108-R05522805-1.pdf: 7617405 bytes, checksum: 5522845ee79757c21e77751e3bee987f (MD5) Previous issue date: 2019 | en |
dc.description.tableofcontents | 誌謝 i
中文摘要 ii Abstract iii 目錄 i 圖目錄 iii 表目錄 viii 符號表 ix 1 第一章、緒論 1 1.1 研究動機與目的 1 1.2 文獻回顧 3 1.3 本文貢獻 6 1.4 論文章節摘要 7 2 第二章、應用程式背景技術與相關研究 9 2.1 Android手機作業系統 9 2.2 Android整合開發環境與Android Studio 10 2.3 Java程式語言 12 2.4 Xml標記式語言 14 2.5 Google Maps API開發工具 14 2.6 JSON資料交換格式 26 2.7 導航相關應用程式研究 28 3 第三章、多動力馬達電動車之系統分析 32 3.1 多動力馬達電動車架構 32 3.2 馬達及馬達驅動器 33 3.3 傳動齒輪箱 40 3.4 輪胎模型 41 3.5 車體動態模型 46 3.6 電池模型 52 4 第四章、聯網節能路線規劃系統 56 4.1 馬達特性與車輛直行方程推導 56 4.2 車速曲線模型建立 59 4.3 電動車直行情境之能耗方程推導 63 4.4 聯網節能路線規劃系統流程 68 4.5 MIL行車模擬分析 76 5 第五章、Android導航應用程式實作成果展示 95 5.1 程式開發環境 95 5.2 操作頁面展示 95 6 第六章、二階段聯網即時節能策略 117 6.1 多動力馬達電動車發展 117 6.2 駕駛者旅次行為分析 118 6.3 二階段聯網即時節能策略流程 119 7 第七章、實車實驗驗證 135 7.1 實車實驗之硬體介紹 135 7.2 底盤動力計平台架構 136 7.3 底盤動力計實驗 138 7.4 上路實驗 144 8 第八章、結論與未來展望 151 8.1 結果討論 151 8.2 導航應用程式產品介紹與安裝步驟 153 8.3 未來展望 161 參考文獻 162 | |
dc.language.iso | zh-TW | |
dc.title | 多動力馬達電動車聯網路線規劃系統與即時節能動力分配策略 | zh_TW |
dc.title | Networked Route Planning System and Real-time Energy Saving Strategy for an Electric Vehicle Driven by Multiple Motors | en |
dc.type | Thesis | |
dc.date.schoolyear | 107-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蕭得聖(Te-Sheng Hsiao),李綱(Kang Li) | |
dc.subject.keyword | 電動車,節能行車策略,導航Android應用程式,Google Maps API,節能路線規劃, | zh_TW |
dc.subject.keyword | Electric vehicle,Power distribution,Navigation Android Application,Google Maps API,energy-efficient route planning, | en |
dc.relation.page | 168 | |
dc.identifier.doi | 10.6342/NTU201900480 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2019-02-12 | |
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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