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  1. NTU Theses and Dissertations Repository
  2. 工學院
  3. 機械工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63008
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dc.contributor.advisor李綱(Kang Li)
dc.contributor.authorChi-Wen Chenen
dc.contributor.author陳麒文zh_TW
dc.date.accessioned2021-06-16T16:18:34Z-
dc.date.available2016-02-01
dc.date.copyright2013-03-06
dc.date.issued2013
dc.date.submitted2013-02-04
dc.identifier.citation1. Miller, J.H., Solar Cooling System for an Automobile, 1976: U.S.
2. Shum, S., Solar Powered Automobile Cooling System, 1987: U.S.
3. Snow, C.E., Solar Powered Heating and Ventilation System for Vehicle, 2004: U.S.
4. Kil Sang Jang, D.W.L., Solar Cell System for Vehicle and Control Method Thereof, 2012: U.S.
5. Lin, T.-H., Research on Solar Air-Conditioning System for Direct Driving. 2011.
6. Huang, B.J., F.S. Sun, and R.W. Ho, Near-maximum-power-point-operation (nMPPO) design of photovoltaic power generation system. Solar Energy, 2006. 80(8): p. 1003-1020.
7. Allegro Specification of ACS758, 2012.
8. IRF 2804 AUTOMOTIVE MOSFET.
9. Tonui, J.K. and Y. Tripanagnostopoulos, Improved PV/T solar collectors with heat extraction by forced or natural air circulation. Renewable Energy, 2007. 32(4): p. 623-637.
10. Ward, T.A., Hybrid Vehicle With A Low Voltage solar Panel Charging A High Voltage Battery Using A Series Charger To Separately Charge Individual Cells Of the Series Connected Battery 2011: U.S.
11. Chaoui, H., P. Sicard, and H.J.N. Ndjana, Adaptive state of charge (SOC) estimation for batteries with parametric uncertainties in Advanced Intelligent Mechatronics2010: Montreal, ON.
12. McIntyre, M., et al., Adaptive State of Charge (SOC) Estimator for a Battery, in American Control Conference2006: Minneapolis, MN. p. 5740-5744.
13. He, H., R. Xiong, and J. Fan, Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach. Energies, 2011. 4(4): p. 582-598.
14. Chaturvedi, N.A., et al., Algorithms for Advanced Battery-Management Systems MODELING, ESTIMATION, AND CONTROL CHALLENGES FOR LITHIUM-ION BATTERIES. Ieee Control Systems Magazine, 2010. 30(3): p. 49-68.
15. Di Domenico, D., A. Stefanopoulou, and G. Fiengo, Lithium-Ion Battery State of Charge and Critical Surface Charge Estimation Using an Electrochemical Model-Based Extended Kalman Filter. Journal of Dynamic Systems Measurement and Control-Transactions of the Asme, 2010. 132(6).
16. Smith, K.A., C.D. Rahn, and C.Y. Wang, Model-Based Electrochemical Estimation and Constraint Management for Pulse Operation of Lithium Ion Batteries. Ieee Transactions on Control Systems Technology, 2010. 18(3): p. 654-663.
17. Santhanagopalan, S. and R.E. White, Online estimation of the state of charge of a lithium ion cell. Journal of Power Sources, 2006. 161(2): p. 1346-1355.
18. He, H.W., et al., Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles. Energy, 2012. 39(1): p. 310-318.
19. Habiballah, R.E. and C. Mo-Yuen, Adaptive ParameterIdentification and State-of-Charge Estimation of Lithium-Ion Batteries, in IEEE Industrial Electronics Society2012: Montreal, Canada.
20. Shen, Y.Q., Adaptive online state-of-charge determination based on neuro-controller and neural network. Energy Conversion and Management, 2010. 51(5): p. 1093-1098.
21. Chiang, Y.H., W.Y. Sean, and J.C. Ke, Online estimation of internal resistance and open-circuit voltage of lithium-ion batteries in electric vehicles. Journal of Power Sources, 2011. 196(8): p. 3921-3932.
22. Åström, K.J. and B.r. Wittenmark, Adaptive control. 2nd ed. Dover books on engineering. 2008, Mineola, N.Y.: Dover Publications. xvi, 573 p.
23. Ioannou, P.A. and B. Fidan, Adaptive control tutorial. Advances in design and control. 2006, Philadelphia, PA: Society for Industrial and Applied Mathematics. xvi, 389 p.
24. Fisher, T. Interactive Digital Filter Design. Available from: http://www-users.cs.york.ac.uk/~fisher/mkfilter/.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/63008-
dc.description.abstract本碩士論文之研究目的為開發一套適合電動車使用之太陽能空調系統,以降低空調系統對於電動車之耗能負擔。本研究使用兩片發電量二百三十瓦的太陽能板與一具額定功率一百五十瓦之壓縮機開發一套十二伏特太陽能驅動之冷氣系統,此系統包含冷氣空調、電池管理與能源管理三個子系統,每一個子系統都包含了一個自製的嵌入式控制器。所有系統軟/硬體及韌體的設計、製作、測試與分析都會在本論文中詳細描述與討論。
本研究所開發之電動車用太陽能冷氣系統經過實驗運轉測試與分析後,可歸納出此系統具備以下幾項特色:
1. 本系統使用台大新能源中心開發之nMPPO(near Maximum Power Point Opeartion)太陽光發電控制技術,減少太陽光發電系統之硬體成本及損耗所可能造成的不確定性;
2. 透過電力電子控制技術,並利用鋰電池輔助太陽電池以提供冷氣系統壓縮機啟動所需之大電流(可高達100安培),當太陽光發電量充足時,可直接以太陽光發電驅動冷氣機運轉,並將多餘的電能儲存在鋰電池,當太陽光發電量不足時,可以鋰電池輔助供電給冷氣機,以確保冷氣系統可在太陽光發電量擾動情形下亦能平順地運轉;
3. 為了延長冷氣機在太陽光發電量不足或不穩定下之運轉時間與提升系統可靠度,本系統可利用現有車用鉛酸電池(低壓)作為額外的供電來源,該鉛酸電池可由電動車之動力電池(高壓)保持其電壓維持在一穩定範圍內,除可在鋰電池(低壓)電量不足時輔助供電給冷氣機使用,亦可與鋰電池(低壓)共同作為太陽電池與冷氣機間之緩衝,發揮穩定電壓與保護冷氣機之功能,以提昇本系統抵抗太陽光輻射量擾動之強健性;此外,鉛酸電池提供給冷氣使用之電能亦可在太陽輻射量充足時由太陽光發電補充,藉此可提高本系統之太陽能能源替代率;
4. 本系統透過自行研發之電池管理與能量管理整合控制技術,可在冷氣機運轉下同時對鋰電池芯/模組進行電量平衡工作。在電池芯/模組高電量狀態下,能量控制器將輸出電壓保持在直流/交流逆變器的輸入電壓範圍內和電池的充放電控制,除可供應冷氣機電源,電池管理系統可同時對鋰電池芯/模組進行平衡。
5. 本系統之冷氣機控制透過擾動式搜尋法,搜尋最佳之冷氣機效能係數(Coefficient of Performance, COP),並透過蒸發器之風速控制,將冷氣機之COP值盡可能控制在此最佳值,根據2012年12月~2013年1月所收集之實驗數據顯示,在外界環境溫度約攝氏25度、蒸發器出風口溫度約攝氏17度下,COP平均值可達2.0左右,若是在較高環境溫度下,COP值可再更高。
zh_TW
dc.description.abstractThe goal of this research is to develop a solar powered air-conditioner for electric vehicles (EVs) to reduce the energy consumption load of air-conditioning to batteries. In this thesis, two 230W photovoltaic modules and a 150W compressor were adopted to develop a 12V solar powered air-conditioner. The system consistss of three sub-systems an air-conditioner, a battery management system and an energy management system, which all employed a self-made embedded controller. The details about the design, development, tests and evaluation of the system’s hardware,firmware and software will be presented and discussed.
Experimental tests and data analysis reveal that the developed solar powered air-conditioning system has the following features:
1. The system utilizes the novel solar PV control technique dubbed nMPPO (near Maximum Power Point Operation), which was developed by the NTU New Energy Center., to reduce the hardware cost and uncertainty due to wear of hardware components.
2. Through power electronics control techniques and the use of lithium-ion batteries for aiding solar batteries in providing high currents (up to 100A) to start the compressor of the air-conditioner, the air-conditioner is able to be directly driven by solar PV panels as the power generation of solar PV panels is high. Also, the excess electrical energy generated by solar PV panels can be saved in the lithium-ion batteres. As the solar PV power generation is low, lithium-ion batteries can provide ancillary electric power for the air-conditioner to make the system be able to smoothly operate in the face of solar power generation fluctuation.
3. In order to extend the run time of the air-conditioner in poor or unstable solar power generation conditions and improve the reliability of the system, the existing lead-acid batteries (low voltage) can be incorporated into the system to provide extra electic power. The lead-acid batteries are charged by the EV power batteries (high voltage) to maintain the voltage in a certain, steady range. Besides providing ancillary electric power, the lead-acid batteries function as the buffer between solar batteries and the air-conditioner to protect and stabilize the input voltage to the air-conditioner along with lithium-ion batteries, thereby the system’s robustness against the fluctuation of solar power generation can be enhanced. In addition, the electric energy consumed by the air-conditioner can be restored to lead-acid batteries by the excess solar PV power, so that the green energy substitution rate can be increased.
4. Through integraton of self-developed battery management and energy management control techniques, the state of charge (SOC) of lituium-ion batteries can still be balanced while the air-conditioner is running. In high SOC status, the energy management controller keeps its output voltage within the input voltage range of the DC/AC inverter, so that the air-conditioner can be charged while the battery management system can apply balanced charging to the lithium-ion batteries.
5. The air-conditioner controller employs a perturbation search algoroithm to explore the optimal coefficient of performance (COP) point and use it as the reference operation point for the air-conditioner through output flow control of evaporator. According to the experimental data collected in December, 2012 ~January, 2013, the COP of the developed solar air-conditioning system is able to reach ~2.0 in the environment temperature of 25 degrees Celsius with the evaporator output flow temperature of 17 degrees Celsius. Note that the value of the COP can be larger in higher environmental temperature.
en
dc.description.provenanceMade available in DSpace on 2021-06-16T16:18:34Z (GMT). No. of bitstreams: 1
ntu-102-R99522843-1.pdf: 20773225 bytes, checksum: 8fd2522a2c25871ce60b8989a3aa1061 (MD5)
Previous issue date: 2013
en
dc.description.tableofcontents口試委員會審定書 i
誌謝 iii
中文摘要 v
ABSTRACT vii
CONTENTS xi
LIST OF FIGURES xiv
LIST OF TABLES xxiv
Chapter 1 Introduction 1
1.1 Research Motivation & Research Goals 1
1.2 Literature Review 1
1.3 Research 7
1.4 Thesis Architecture 8
Chapter 2 Design and Analysis of the Air Cooling Subsystem 11
2.1 Overview of the Air Cooling Subsystem 11
2.2 Hardware/Software Architecture of the Air Cooling Subsystem 12
2.2.1 Hardware Architecture of the Air Cooling Machine 12
2.2.2 Hardware Design of the Air Cooling Controller 17
2.2.3 Tuning Software of the Air Cooling Controller 25
2.3 Coefficient of Performance Tracking and the Analysis of the Air Cooling Subsystem 27
2.3.1 Result of Steady State Testing of Air Cooling Subsystem 30
2.3.2 Tracking Maximum Coefficient of Performance Algorithm 36
2.3.3 Experiment Result of Tracking Maximum Coefficient of Performance 37
Chapter 3 Design of Battery Management and Data Acquisition Systems for Lithium-Ion Batteries 41
3.1 Hardware/Software Architecture of the Lithium Battery Management and Data Acquisition Subsystem 41
3.1.1 Hardware Design of the Lithium Battery Management and Data Acquisition Subsystem 43
3.1.2 Data Acquisition Software Design of the Lithium Battery Management and Data Acquisition Subsystem 53
3.2 The Cell Equalization Algorithm of the Lithium-ion Battery Management System 56
3.2.1 Cell Equalization Algorithm 56
Chapter 4 Design of the Central Energy Management System 59
4.1 Architecture of the Central Energy Management System 61
4.1.1 Hardware Design of the Central Energy Management Subsystem 61
4.1.2 PC-Based Monitor Software of the Central Energy Management Subsystem 70
4.2 State Machine Design for the Central Energy Management System 71
4.2.1 The Electric Circuit of Power Switching Control 72
4.2.2 Discussion of the Special Conditions of Energy Deployment 76
4.2.3 Control State Machine of Energy Management Subsystem 79
Chapter 5 Evaluation of Direct Solar PV Driven Air Conditioning System 89
5.1 Architecture of the Solar Powered Air Conditioning System 89
5.2 Verification of the Control State Machine shown in 4.2.3 93
5.3 Evaluation and Analysis of the Experiment Results of Solar Powered Air Cooling System for Electric Vehicle 106
5.4 Design Rule for Determining Capacity of Lithium Battery Pack, Watt of Photovoltaic Modules and Allowable Power Consumption of Air Cooling 156
Chapter 6 Conclusion and Future Work 161
6.1 Conclusion 161
6.2 Contribution 162
6.3 Future Work 162
Appendix A Schematic Sheets of Controllers 165
Appendix B Adaptive System Identification Algorithm of Open Circuit Voltage Estimation 191
B.1 Introduction of the Lithium Battery Model 191
B.2 Adaptive System Identification Algorithm of Open Circuit Voltage Estimation 196
Appendix C Main Function of Controllers 203
C.1 Main Function of Air Cooling Controller 203
C.2 Main Function of Energy Management Controller 212
C.3 Main Function of Battery Management Controller 227
REFERENCE 235
dc.language.isoen
dc.subject太陽能直驅冷氣機zh_TW
dc.subject鋰電池資料擷取系統zh_TW
dc.subject能量管理控制器zh_TW
dc.subject鋰電池管理控制器zh_TW
dc.subject電動車zh_TW
dc.subject冷氣機控制器zh_TW
dc.subject嵌入式控制系統zh_TW
dc.subject電力控制策略zh_TW
dc.subjectEnergy Management Controlleren
dc.subjectDirect Solar-Driven Air-Conditioneren
dc.subjectElectric Power Control Strategyen
dc.subjectData Acquisition System for Lithium-ion Batteryen
dc.subjectAir Cooling Controlleren
dc.subjectLithium-ion Battery Management Controlleren
dc.subjectElectric Vehiclesen
dc.subjectEmbedded Control Systemen
dc.title電動車太陽能冷氣機研製zh_TW
dc.titleDesign, Implementation and Evaluation of a Solar Powered Air-Conditioner for Electric Vehiclesen
dc.typeThesis
dc.date.schoolyear101-1
dc.description.degree碩士
dc.contributor.coadvisor黃秉鈞(Bin-Juine Huang)
dc.contributor.oralexamcommittee顏瑞和,李坤彥
dc.subject.keyword電動車,太陽能直驅冷氣機,鋰電池資料擷取系統,電力控制策略,冷氣機控制器,鋰電池管理控制器,能量管理控制器,嵌入式控制系統,zh_TW
dc.subject.keywordElectric Vehicles,Direct Solar-Driven Air-Conditioner,Electric Power Control Strategy,Data Acquisition System for Lithium-ion Battery,Air Cooling Controller,Lithium-ion Battery Management Controller,Energy Management Controller,Embedded Control System,en
dc.relation.page236
dc.rights.note有償授權
dc.date.accepted2013-02-04
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept機械工程學研究所zh_TW
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