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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 林巍聳(Wei-Song Lin) | |
| dc.contributor.author | Zhong-Ting Cai | en |
| dc.contributor.author | 蔡忠庭 | zh_TW |
| dc.date.accessioned | 2021-06-15T12:54:56Z | - |
| dc.date.available | 2021-07-26 | |
| dc.date.copyright | 2016-07-26 | |
| dc.date.issued | 2016 | |
| dc.date.submitted | 2016-07-15 | |
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Morello, 'Cooperative driving: basic concepts and a first assessment of 'intelligent cruise control' strategies,' in Proc. Advanced Telematics in Road Transport, vol. 11, DRIVE Conference, Brussels, Belgium, pp. 908-929, Feb 1991. [8] M. Persson, F. Botling, E. Hesslow, and R. Johansson, 'Stop and go controller for adaptive cruise control,' in Proceedings of the 1999 IEEE Int. Conf. on Control Applications and IEEE Int. Symp. Computer-Aided Control System Design, pp. 1692-1697, 1999. [9] Y. Kyongsu, M. Ilki, and K. Young Do, 'A vehicle-to-vehicle distance control algorithm for stop-and-go cruise control,' in IEEE intelligent transportation systems conference proceedings, pp. 478-482, 2001. [10] S. Moon, I. Moon, and K. Yi, 'Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance,' Control Engineering Practice, vol. 17, pp. 442-455, 2009. [11] G. J. L. Naus, J. Ploeg, M. J. G. Van de Molengraft, W. P. M. H. Heemels, and M. Steinbuch, 'Design and implementation of parameterized adaptive cruise control: An explicit model predictive control approach,' Control Engineering Practice, vol. 18, pp. 882-892, 2010. [12] J. Ploeg, B. T. M. Scheepers, E. van Nunen, N. van de Wouw, and H. Nijmeijer,'Design and experimental evaluation of cooperative adaptive cruise control,' in 14th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 260-265, 2011. [13] C. C. Chan and K. T. Chau, Modern Electric Vehicle Technology: Oxford University Press, 2001. [14] M. Ehsani, Y. Gao, and A. Emadi, Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design, Second Edition: CRC Press, 2010. [15] K. El Majdoub, F. Giri, H. Ouadi, L. Dugard, and F. Z. Chaoui, 'Vehicle longitudinal motion modeling for nonlinear control,' Control Engineering Practice, vol. 20, pp. 69-81, 2012. [16] B. Ganji, A. Z. Kouzani, S. Y. Khoo, and M. Shams-Zahraei, 'Adaptive cruise control of a HEV using sliding mode control,' Expert Systems with Applications, vol. 41, pp. 607-615, 2/1/ 2014. [17] C.-C. Tsai, S.-M. Hsieh, and C.-T. Chen, 'Fuzzy Longitudinal Controller Design and Experimentation for Adaptive Cruise Control and Stop&Go,' Journal of Intelligent & Robotic Systems, vol. 59, pp. 167-189, 2010. [18] Q. Chengqun, 'A design of automobile cruise control system based on fuzzy PID,' in International Conference on Information Science, Electronics and Electrical Engineering (ISEEE), pp. 450-452, 2014. [19] W.-S. Lin, 'Optimality and convergence of adaptive optimal control by reinforcement synthesis,' Automatica, vol. 47, pp. 1047-1052, 2011. [20] J. Wenger, 'Automotive radar - status and perspectives,' in IEEE Compound Semiconductor Integrated Circuit Symposium, 2005. CSIC '05, p. 4, 2005. [21] J. Hasch, E. Topak, R. Schnabel, T. Zwick, R. Weigel, and C. Waldschmidt, 'Millimeter-Wave Technology for Automotive Radar Sensors in the 77 GHz Frequency Band,' IEEE Transactions on Microwave Theory and Techniques, vol. 60, pp. 845-860, 2012. [22] B. E. GmbH, 'Bosch Engineering Long-Range-Radar LRR3: Radar sensor for railway applications,' http://www.bosch-engineering.de, June 6, 2016, 2010. [23] A. Watts, A. Vallance, A. Whitehead, C. Hilton, and A. Fraser, 'The Technology and Economics of In-Wheel Motors,' SAE Int. J. Passeng.Cars-Electron. Elect. Syst., vol. 3, no. 2, pp. 37-57, 2010. [24] N. Hashemnia and B. Asaei, 'Comparative study of using different electric motors in the electric vehicles,' in Electrical Machines, 2008. ICEM 2008. 18th International Conference on, pp. 1-5, 2008. [25] M. Anderson and D. Harty, 'Unsprung Mass with In-Wheel Motors - Myths and Realities,' AVEC 10, UK, 2010. [26] L.Evans and J.MacIsaac, 'NHTSA Tire Fuel Efficiency Consumer Information Program Development: Phase 2 –Effects of Tire Rolling Resistance Levels on Traction, Treadwear, and Vehicle Fuel Economy,' United States, 2009. [27] T. D. Gillespie, Fundamentals of Vehicle Dynamics: Society of Automotive Engineers, 1992. [28] A. A. o. S. Highway and T. Officials, A Policy on Geometric Design of Highways and Streets, 2001: American Association of State Highway and Transportation Officials, 2001. [29] C. Bohn and D. P. Atherton, 'An analysis package comparing PID anti-windup strategies,' IEEE Control Systems, vol. 15, pp. 34-40, 1995. [30] A. S. Hodel and C. E. Hall, 'Variable-structure PID control to prevent integrator windup,' IEEE Transactions on Industrial Electronics, vol. 48, pp. 442-451, 2001. [31] A. Visioli, 'Modified anti-windup scheme for PID controllers,' IEE Proceedings - Control Theory and Applications, vol. 150, pp. 49-54, 2003. [32] L. A. 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| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/50728 | - |
| dc.description.abstract | 適應性巡航控制(Adaptive Cruise Control, ACC)系統是實現自動駕駛的一項關鍵技術，車輛搭載ACC系統可以代替駕駛操作反覆的車速控制，因此可以減輕駕駛的注意力和視力負荷，然而現有的ACC系統存在下列幾個問題：1. 無法適用於各種駕駛情境；2. 車間距離過大無法達到提升道路吞吐量的目的，且容易面臨車輛插隊(Cut-in)的情境；3. 頻繁的加減速導致消耗額外的能量。
本論文以使用輪轂直流無刷馬達為動力的電動車為研究對象，設想毫米波雷達、動力總成、車輛等規格和參數齊備，用適應最佳控制演算法結合模糊PID控制器構成ACC系統的自優化適應性巡航控制器，以和前車的間隔時間(Headway time)和碰撞時間的倒數(Inverse Time To Collision, ITTC)做為模糊邏輯的前件部輸入，適應最佳控制演算法以優化跟車性能和能源效率為目標，透過不同的試驗行駛自動優化各模糊規則之下的PID控制器參數。 本論文用電腦模擬驗證ACC系統的自優化適應性巡航控制器，透過US06行車型態及多種情境的訓練自動優化各模糊規則的PID參數，訓練完成的控制器在UDDS、HWFET、US06、LA92行車型態，以及車輛插隊、停再開(Stop & Go)、追上前車時進行減速並跟隨前車的模擬情境下都能達成目標，且結果顯示使用自優化適應性巡航控制器和模糊邏輯控制器相比，皆能以較小的累計誤差及較高的能源效率完成任務。 | zh_TW |
| dc.description.abstract | Adaptive cruise control (ACC) system is a key component of automotive autopilot. It assists the driver with automatic speed control that lessens driver’s burden in attention and vision. However, several shortcomings appear in the existing ACC system. First, the system is not applicable to many driving scenarios that the driver may encounter. Second, a large headway distance is necessary that diminishes road throughput and may incur cut-in situations. Third, frequent acceleration and deceleration makes the vehicle consume more energy. This thesis presents the self-optimizing adaptive cruise controller that can maintain vehicle speed under various driving resistance, follow leading car even in stop-and-go, and prevent from any collision while a car cut-in. This innovative design is developed on an in-wheel motor-powered electric vehicle that has a front millimeter-wave radar to detect leading car’s relative speed and distance. The self-optimizing adaptive cruise controller consists of a fuzzy PID controller and the adaptive optimal control (AOC) algorithm. Particularly, premise inputs are headway time and inverse time-to-collision (ITTC). Fuzzification actually divides the operating points of the vehicle system into several linear regions, each associated with a PID control law. The AOC algorithm is dedicated to adjust the PID parameters for achieving better cruising performance and energy efficiency. On a simulation system, the proposed design is examined in driving cycles such as UDDS, HWFET, US06, and LA92, including scenarios such as cut-in, stop & go, and car following. The self-optimizing adaptive cruise controller succeeds in every driving cycle and scenario, and outperforms a fuzzy logic controller in term of accumulated error and energy efficiency. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T12:54:56Z (GMT). No. of bitstreams: 1 ntu-105-R03921001-1.pdf: 2340149 bytes, checksum: c2ddcbd10dff5e43705387ad42925a99 (MD5) Previous issue date: 2016 | en |
| dc.description.tableofcontents | 口試委員會審定書........................................... i
誌謝 ..................................................... ii 中文摘要 ................................................ iii Abstract.................................................. iv 目錄 ..................................................... vi 圖目錄 ................................................... ix 表目錄 .................................................. xii 第一章 緒論 ............................................... 1 1.1 適應性巡航控制 .................................. 1 1.1.1 適應性巡航控制簡介 ....................... 1 1.1.2 適應性巡航控制的發展史 ................... 2 1.2 研究動機與文獻回顧 .............................. 5 1.2.1 研究動機 ................................. 5 1.2.2 適應性巡航控制器設計文獻回顧 ............. 6 1.3 章節介紹 ....................................... 10 第二章 前置雷達之輪轂馬達電動車 .......................... 11 2.1 車用雷達 ....................................... 11 2.2 輪轂馬達電動車 ................................. 16 2.3 車輛行駛阻力 ................................... 23 2.4 適應性巡航控制系統及電動車加速度之數學模型 ..... 29 2.4.1 電動車加速度之數學模型 .................. 29 2.4.2 適應性巡航控制之數學模型 ................ 29 第三章 前置雷達電動車之自優化適應性巡航控制器............. 31 3.1 李亞普諾夫理論 ................................. 32 3.1.1 李亞普諾夫理論簡介 ...................... 32 3.1.2 李亞普諾夫穩定性定理 .................... 32 3.2 PID控制器....................................... 33 3.2.1 PID控制器簡介............................ 33 3.3 模糊理論 ....................................... 36 3.3.1 模糊理論簡介 ............................ 36 3.3.2 模糊化 .................................. 37 3.3.3 模糊知識庫 .............................. 39 3.3.4 模糊推理引擎 ............................ 42 3.3.5 解模糊化 ................................ 42 3.4 適應最佳控制 ................................... 43 3.4.1 最佳控制簡介 ............................ 43 3.4.2 最佳控制之必要條件 ...................... 46 3.4.3 適應最佳控制之自優化策略 ................ 48 3.5 輻狀基底函數類神經網路 ......................... 54 3.5.1 類神經網路簡介 .......................... 54 3.5.2 類神經網路的分類 ........................ 56 3.5.3 輻狀基底函數類神經網路 .................. 59 3.6 前置雷達電動車之自優化適應性巡航控制器 ......... 63 3.6.1 速度控制器設計 .......................... 65 3.6.2 模糊PID控制器............................ 70 3.6.3 模糊PID控制器之自優化策略................ 75 第四章 電腦模擬與驗證 .....................................80 4.1 適應性巡航控制系統之模擬架構 ................... 80 4.1.1 行車型態測試簡介 ........................ 81 4.1.2 訓練程序 ................................ 84 4.2 適應性巡航控制系統之巡航性能分析 ............... 90 4.2.1 傳統巡航控制之性能分析 .................. 90 4.2.2 適應性巡航控制之性能分析 ................ 91 4.2.3 速度控制器對環境參數變動之性能分析...... 109 4.3 適應性巡航控制系統之能源效率分析 .............. 111 4.3.1 UDDS行車型態測試........................ 112 4.3.2 HWFET行車型態測試....................... 114 4.3.3 US06行車型態測試........................ 117 4.3.4 LA92行車型態測試........................ 119 4.3.5 巡航性能及能源效率分析總結 ............. 122 第五章 結論及未來展望 ................................... 123 5.1 結論 .......................................... 123 5.2 未來展望 ...................................... 123 參考文獻 .................................................124 | |
| dc.language.iso | zh-TW | |
| dc.subject | 電動車 | zh_TW |
| dc.subject | 適應最佳控制 | zh_TW |
| dc.subject | 適應性巡航控制 | zh_TW |
| dc.subject | 模糊PID控制器 | zh_TW |
| dc.subject | 自主優化 | zh_TW |
| dc.subject | 適應最佳控制 | zh_TW |
| dc.subject | 自主優化 | zh_TW |
| dc.subject | 電動車 | zh_TW |
| dc.subject | 模糊PID控制器 | zh_TW |
| dc.subject | 適應性巡航控制 | zh_TW |
| dc.subject | Self-optimizing controller | en |
| dc.subject | Electric vehicle | en |
| dc.subject | Adaptive cruise control | en |
| dc.subject | Fuzzy PID controller | en |
| dc.subject | Adaptive optimal control | en |
| dc.subject | Self-optimizing controller | en |
| dc.subject | Electric vehicle | en |
| dc.subject | Adaptive cruise control | en |
| dc.subject | Fuzzy PID controller | en |
| dc.subject | Adaptive optimal control | en |
| dc.title | 前置雷達電動車之自優化適應性巡航控制器 | zh_TW |
| dc.title | Design of Self-Optimizing Adaptive Cruise Controller for Radar-Guided Electric Vehicle | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 104-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 鍾鴻源,廖德誠,施慶隆,張國維 | |
| dc.subject.keyword | 電動車,適應性巡航控制,模糊PID控制器,適應最佳控制,自主優化, | zh_TW |
| dc.subject.keyword | Electric vehicle,Adaptive cruise control,Fuzzy PID controller,Adaptive optimal control,Self-optimizing controller, | en |
| dc.relation.page | 126 | |
| dc.identifier.doi | 10.6342/NTU201600927 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2016-07-18 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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