锂离子电池SOC预测方法应用研究
|
摘要
电池的剩余电量(也称荷电状态,State of charge,SOC)预测是电池管理系统中最基础、最重要的部分。电池荷电状态的准确监测不仅仅能够为电池设备使用者提供电池能量供给状况,它还是电池管理系统中充放电管理、均衡控制管理的基础。因此怎样准确预测电池SOC的值意义重大。
本文以锂离子电池为研究对象,对锂离子电池的荷电状态预测算法进行研究。通过对锂电池的工作原理进行分析,从而了解电池电量的产生及变化机理,在此基础上对电池进行充电、放电特性的研究,研究过程中考虑电池电流、温度等因素对电池电量的影响方式,最后在结合分析自放电率、循环次数及工作状态等其它的影响因素,提出将SOC分为三种状态进行估算,将扩展卡尔曼滤波算法,开路电压法、安时法相结合;通过对电压曲线的变化规律及电池充放电效率分析,提出了以库仑效率为基础的电量累积量和动态变化量的计算方法,以此对安时法进行改进,建立较为准确的电池空间模型,从而完成SOC的计算。
最后以SE60AHA型号锂电池为实验对象,进行实际充放电试验。试验过程中在电池的正常充放电、对电流增加噪声干扰以及对SOC值增加初始误差三种情况下,将本文提出的方法与传统方法进行对比,结果表明本文所采用的方法不仅能提高SOC的估算精度,对电流噪声及初始误差也有很强的抑制和修正作用。
In the battery management system, the state of charge (SOC) forecast is the most basic and most important part. The precise estimation of SOC is not only able to provide users with battery power supply situation, it is also the foundation of charging-discharging management and balance control in battery management system.Therefore, how to accurately predict the value of SOC is great significance.
Prevention at lithium-ion battery level, this paper is to research the forecasting algorithm of SOC. By the analysis of lithium-ion battery working principle, the emergence and change mechanism of electric quantity can be understood, based on this the battery charge and discharge characteristics was studied and in the process how do the battery current, temperature and other factors effecting on SOC was considered which lay the foundation for estimate of SOC, in the end with analysis of other factors which affect SOC algorithm like self-discharge rate, cycle number and working conditions, This paper describes a new method that by dividing battery into three states, the different algorithm, extended Kalman filter algorithm, open-circuit voltage method and Ah counting method were combined to predict SOC, through the analysis of battery charge-discharge efficiency and regularity for change of the voltage curve, a computing method which was about dynamic changing capacity and accumulation capacity based on coulomb efficiency was gave to improve the Ah counting, then based on this, a more accurate battery-space model was established. Thus the calculation of SOC was completed.
In the end, the actual charge-discharge test based on SE60AHA type lithium batteries was accomplished in this paper. During the experiment, the method proposed in this paper was compared with the traditional method under three kinds of conditions, making normal charging and discharging experiment, increasing noise interference on current and changing the value of the SOC initial, in the results, the method used in this paper can not only improve the SOC precision, but also can suppress the noise and correct the initial error.
本文以锂离子电池为研究对象,对锂离子电池的荷电状态预测算法进行研究。通过对锂电池的工作原理进行分析,从而了解电池电量的产生及变化机理,在此基础上对电池进行充电、放电特性的研究,研究过程中考虑电池电流、温度等因素对电池电量的影响方式,最后在结合分析自放电率、循环次数及工作状态等其它的影响因素,提出将SOC分为三种状态进行估算,将扩展卡尔曼滤波算法,开路电压法、安时法相结合;通过对电压曲线的变化规律及电池充放电效率分析,提出了以库仑效率为基础的电量累积量和动态变化量的计算方法,以此对安时法进行改进,建立较为准确的电池空间模型,从而完成SOC的计算。
最后以SE60AHA型号锂电池为实验对象,进行实际充放电试验。试验过程中在电池的正常充放电、对电流增加噪声干扰以及对SOC值增加初始误差三种情况下,将本文提出的方法与传统方法进行对比,结果表明本文所采用的方法不仅能提高SOC的估算精度,对电流噪声及初始误差也有很强的抑制和修正作用。
In the battery management system, the state of charge (SOC) forecast is the most basic and most important part. The precise estimation of SOC is not only able to provide users with battery power supply situation, it is also the foundation of charging-discharging management and balance control in battery management system.Therefore, how to accurately predict the value of SOC is great significance.
Prevention at lithium-ion battery level, this paper is to research the forecasting algorithm of SOC. By the analysis of lithium-ion battery working principle, the emergence and change mechanism of electric quantity can be understood, based on this the battery charge and discharge characteristics was studied and in the process how do the battery current, temperature and other factors effecting on SOC was considered which lay the foundation for estimate of SOC, in the end with analysis of other factors which affect SOC algorithm like self-discharge rate, cycle number and working conditions, This paper describes a new method that by dividing battery into three states, the different algorithm, extended Kalman filter algorithm, open-circuit voltage method and Ah counting method were combined to predict SOC, through the analysis of battery charge-discharge efficiency and regularity for change of the voltage curve, a computing method which was about dynamic changing capacity and accumulation capacity based on coulomb efficiency was gave to improve the Ah counting, then based on this, a more accurate battery-space model was established. Thus the calculation of SOC was completed.
In the end, the actual charge-discharge test based on SE60AHA type lithium batteries was accomplished in this paper. During the experiment, the method proposed in this paper was compared with the traditional method under three kinds of conditions, making normal charging and discharging experiment, increasing noise interference on current and changing the value of the SOC initial, in the results, the method used in this paper can not only improve the SOC precision, but also can suppress the noise and correct the initial error.
引文
[1]李景虹.先进电池材料[M].北京:学工业出版社.2004.6:1-2
[2]慧琪.基于CAN总线的锂离子动力电池组管理系统[J].机电工程技术,2007,36(1):81-83
[3]贺本林.锂离子电池的新研究[D].兰州大学学位论文,2007.5:4-6
[4]李久芳.电动汽车镍氢电池剩余容量的测试研究[D].武汉理工大学学位论文,2004,5-7
[5]潘靖.锂电池智能管理系统[D].浙江大学硕士学位论文, 2004.3:4-5
[6]廖晓军,何莉萍,钟志华等.电池管理系统国内外现状及其未来发展趋势[J].汽车工程,2006,28(10):961-964
[7]刘均.动力电源管理系统设计与实现[D].哈尔滨工业大学学位论文,2004.6:5-8
[8]乔国艳.电动汽车电池管理系统的研究与设计[D].武汉理工大学硕士论文,2006.4:3-5
[9]刘志勇.电动汽车—中国汽车工业发展的必由之路[J].装备制造技,2009.(4):111-112
[10]宋德良.新排放法规对我国汽车及相关产业的挑战[J].上海汽车,2005,(5):30-32
[11]聂济宇.电动汽车非平稳工况的电源管理系统研究[D].西安交通大学硕士学位论文,2004.3:5-6
[12]张彦琴.混合动力车辆电池性能及其管理系统研究[D].北京工业大学博士论文,2006.9:17-18
[13]马建新,李青松,龚元明等.基于CAN总线的电动汽车蓄电池管理系统[J].机电一体化,2004,5:62-66
[14] Szumanowski,Y.Chang.Battery Management System Based on Battery Nonlinear Dynamics Modeling. IEEE Transactions on Vehicular Technology, 2008, No.3:124-127
[15]王林涛,陈德荣.锂离子电池均衡充电的设计[J].电源技术,2007,73(9):72-73
[16]雷娟,蒋新华,解晶莹.锂离子电池组均衡电路的发展现状[J].电池,2007,37(1) :62-63.
[17] Hande A,Stuart T A,A selective equalizer for Ni-MH batteries[J].J Power Sources,2004,138(1-2):327-339
[18]赵剑.电动汽车蓄电池剩余电量预测方法的研究[D].大连理工大学学位论文,2006,12:3-4
[19]吴友宇,尹叶舟.基于以CAN总线的分布式动力电池管理系统[J].汽车工程.20 04,26(5)::52-54.
[20] Chenghui Ca.State of charge estimation of high power NI-M H rechargeable batte -ry with artificle neural network[C]. Procceedings of the 9th Inetmational Confernceon Neural information Processing .2002. VOL.2:89-93.
[21]李贵海.电池SOC估算策略研究[D].浙江大学硕士学位论文,2006,8:6-7.
[22]邵海岳等.电动汽车用NIMH电池建模及基于状态空间的SOC预测方法[J].汽车工程,2004,26(5):534-537.
[23]美国先进电池联合会(USABC).电动汽车电池实验手册(英文).2001,32-34
[24]麻友良,陈全世,齐占宁.电动汽车用电池SOC定义与检测方法[J].清华大学学报(自然科学版),2001,41(11):453-457
[25]林成涛,王军,平陈全世.电动汽车SOC估计方法原理与应用[J].电池,2004,34(5):376-378.
[26]赵慧勇.车载镍氢电池管理系统研究现状与发展[J].湖北汽车工业学院学报,2004,18(3):1-4.
[27] JaeguIL,SoonjaeL,Namgoong.E“Dynamicst battery model with self- adaptive aging factor for EV and HEV application[C],Proceeding of the15th intermational electric vehicle symposium. San Franc -isco, Calif Electric Vehicle Association of the Americas:1998:57-59
[28]李革臣,古艳磊.电化学阻抗谱法预测锂电池荷电状态[J].电源技术,2008,32(9):599-602.
[29] Holger Blanke,OliverBohlen.Impedance measurements on lead-Cacid batteries for state-of-charge,state-of-health and cranking capability prognosis in electric and hybrid electric vehicles[J]. Journal of Power Sources. 2005.144:418-425
[30]赵徐成,张磊,黄卫星.基于动态电子负载的航空蓄电池内阻与容量关系[J].电源技术,2006,130(2):149-151.
[31] IRYN A,WILLiam R,ERBITS KIY, Battery open-circuit voltage estimation by a method of statistical analysis[J]. Journalof Power Sources 2006,159:1484–1487
[32] V.Pop, H.J.Bergveld. Modeling Battery Behavior for Accurate State-of-Charge Indication[J]. Journal of TheElectroc hemical Society, 2006.153:2013- 2022
[33] H.J. Bergveld, W.S. Kruijt, P.H.L. Notten, in Battery Management Systems Design by Modelling[M], Philips Research Book Series, Kluwer Academic Publishers,2002. vol. 1:48-51
[34]林成涛,王军平,王燕超.用改进的安时计量法估计电动汽车动力电池SOC[J].清华大学学报(自然科学版).2006,46(2):247-251.
[35]刘帅,宁武,王宏利.蓄电池电量监测新技术[J].辽宁工学院学报,2005,35(5):92-295
[36] POP V. Accuracy analysis Of the State-of Charge and remaining run-time determi -nation for lithium-ion batterie[J]. measurement,2008, 10:1016-1022
[37]王斯成,陈子平,杨军.蓄电池剩余容量(SOC)数学模型探讨和在线测试仪的开发[J].太阳能学报,2005,26(1):6-11
[38]李立伟,原明亭,包书哲.基于改进灰色模型的蓄电池剩余容量预测[J].电源技术,2006,130(12):1006-1008
[39] Il-Song Kim. The novel state of charge estimation method for lithium battery using sliding mode observer[J]. Journal of Power Sources. 2006,163:584–590
[40]焦慧敏,余群明.电动车用MH-Ni电池剩余电量的预测研究[J].计算机仿真,2006,23(3):211-214
[41]裴晟,陈全世,林成涛.基于支持向量回归的电池SOC估计方法研究[J].电源技术,2007,31(3):242-244
[42]李革臣,江海,王海英.基于模糊神经网络的电池剩余电量计算模型[J].测试技术学报,2007,21(5)::405-409.
[43] Pritpal Singh, Ramana Vinjamuri , Xiquan Wang. Fuzzy logic modeling of EIS measurements on lithium-ion batteries[J]. Electrochimica Acta . 2006,51:1673–1679
[44]吴红杰,齐铂金,郑敏信等.基于Kalman滤波的镍氢动力电池SOC估算方法[J].北京航空航天大学学报,2007,33(8):945-948.
[45]乐浪,李革臣,朱磊.卡尔曼滤波在电池检测中的应用[J].电源技术,2006,130(2):152-154.
[46] JAEMOON LE,OANYONG N,B.H CHO. Li-ion battery soc estimation method based on the reduced order extended Kalman filtering [J].Journal of PowerSources 2007,17:49–15
[47] Oanyong Nam; B.H. Cho. Li-ion battery SOC estimation method based on the reduced order extended Kalman filtering[J]. Journal of Power Sources; 2007, 174(1):9-15
[48] MorioK ,K azuhiroH ,AnilP Battery SOC and distance to empty of the Honda E VPlus[C].Proceedings of the14th Intenrational Electric Vehicle Symposium. San Franc -isco, Calif Electric Vehicle Association of the Americas:1997:156-159
[49]胡任,韩赞东,王克争.基于BP神经网络预测静置电池的剩余电量[J].电池,2006,36(1):58-59.
[50]齐智,吴锋,陈实.利用人工神经网络预测电池SOC的研究[J].电源技术,2005,29(5):325-328
[51]雷肖,陈清泉,刘开培.电动车电池SOC估计的径向基函数神经网络方法.电工技术学报,2008,23(5):81-87.
[52]陶兴华,陈彪.模糊逻辑与神经网络的蓄电池容量预测[J].电源技术,2004,28(9):578-581
[53] G.Plett.Extended Kalman Filtering for battery management systems of LiPB-based HEV battery packs Part2.Modeling and identificat ion[J].Journal of Power Sources, 2004,134:262-276.
[54] G.Plett.Extended Kalman Filtering for battery management systems of LiPB-based HEV battery packs[J]. Part 1. Background. J. Power Sour,2004,134(2):252-26
[55] Amir Vasebi ,Maral Partovibakhsh, S. Mohammad Taghi Bathaee. A novel combined battery model for state-of-charge estimation in lead-acid batteries based on extended Kalman filter for hybrid electric vehicle applications[J]. Journal of Power Sources.2007, 174:30–40
[56]戴海峰,魏学哲等.基于扩展卡尔曼滤波算法的燃料电池车用锂离子动力电池荷电状态估计[J].机械工程学报,2007,143(2):92-95.
[57]王贵明.电动车动力蓄电池实验建模研究[D].北方工业大学学位论文,2003:6.
[58]刘建国.燃料电池概述[J].物理,2004,33(2):79-83.
[59] D.A.J.Rand,P.T.Moseley等.阀控式铅酸蓄电池.北京:机械工业出版社.郭永榔等译,2007,1-2.
[60]张怀仁.镍氢电池电管理研究[D].国立中山大学学位论文,2005,6:14.
[61]唐有根.镍氢电池[M].北京:化学工业出版社,2007,11-13.
[62]胡仁法,浣上..镍镉电池的通用智能充电控制技术研究[C].中国控制与决策学术年会论文集,沈阳:东北大学出版社,2004,930-932.
[63]黄威.铅酸蓄电池组串联放电均衡控制实验研究[D].长沙理工大学学位论文,2005,4:6-7.
[64]秦爱辉.铅酸蓄电池充电系统研究[D].上海大学学位论文,2008,7-8.
[65]卢汉辉.蓄电池组充电管理系统关键技术的研究[D].上海交通大学学位论文,2007,2:6-7.
[66]郭炳昆.锂离子电池[M].湖南:中南大学出版社,2002:11-12.
[67]黄可龙.锂离子电池原理与关键技术[M].北京:化学工业出版社,2008,7-9.
[68]陈怡平.铅酸与锂离子蓄电池电量估计[D].国立中山大学论文,2007,6:5-7.
[69]栗宇深,汤敏贤,刘炤元．锂电池的原理与应用．电池工业，2004,8(4) :176-180.
[70]吴宇平.锂离子电池:应用与实践[M].北京:化学工业出版社,2004,2-3.
[71]王磊.锂电池充电器芯片的研究与设计[D].厦门大学学位论文,2007,1-2.
[72]李超..电动汽车用镍氢电池模型参数辨识和SOC估算研究[D].天津大学硕士学位论文.2007,2-3
[73]杨军,谢晶莹,王久林.化学电源测试原理与技术[M].北京:化学工业出版社,2006,7-11
[74]蒋新华.锂离子电池组应用电路研究.中国科学院上海微系统与信息技术研究所,2005,1-3.
[75]邓文莲.电动汽车动力电池的计算机管理[D].同济大学学位论文,2005,15-18.
[76]李冬梅.锂离子电池大电流放电分容测试系统的研究.华南理工大学学位论文,2007,7-9.
[77]冯华.电动汽车用电池管理系统的研制[D].北京交通大学学位论文,2007,11-12.
[78]裴锋,黄向东,罗玉涛.电动汽车动力电池变流放电特性与荷电状态实时估计[J].中国电机工程学报,2005,25(9):164-166.
[79]高怀.电动汽车电池管理系统的研究与设计[D].武汉理工大学学位论文,2007,11-12
[80]劳力..动力蓄电池管理系统SOC算法研究[D].北京交通大学学位论文,2007,24-25.
[81]赖世荣..智慧型锂离子电池残存电量之研究[D].国立中山大学学位论文,2004,37-41.
[82]毛宗强.燃料电池[M].北京:化学工业出版社,2005,16-19
[83] Butler J A V.Trans.Faraday Soc[M], Institute of Physical Chemistry, Czechoslovak Academy of Sciences, Prague 1924,19:734
[84] Tafel J Z.Physik.Chem[M], Springer-Verlag, Landolt-B?rnstein-Group IV Physical Chemistry, 1905,50:641
[85]黄文华,韩晓东,陈全世.电动汽车SOC估计算法与电池管理系统的研究[J].汽车工程,2007,29(3):198-201.
[86] Greg Welch. Gary Bishop. An Introduction to the Kalman Filter. Department of Computer Science University of North Carolina at Chapel Hill Chapel Hill, NC 27599-3175.2006.7
[87] R. E. KALMAN. A New Approach to Linear Filtering and Prediction Problems. ASME–Journal of Basic Engineering[J]. 1860.82 (Series D): 35-45.
[88]陈全世,林成涛.电动汽车用电池性能模型研究综述[J].汽车技术,2005,15(3):1-5.
[89]赵兴福.电动汽车蓄电池的建模与仿真研究[D].武汉理工大学硕士学位论文,2004,5-8.
[90] Shriram Santhanagopalan, Ralph E.White.Online estimation of the state of charge of a lithium ion cell. Journal of Power Sources. 2006,161:1346–1355
[91]卢居霄,林成涛,陈全世.三类常用电动汽车电池模型的比较研究[J].电源技术,2006,130(7)::535-538.
[92]王丽芳,胡运飞,廖承林.基于Thevenin改进模型的混合动力镍氢电池SOC估算研究[J].高技术通讯,2008,18(9):948-952.
[93]张术.电动汽车电池管理系统软件设计与SOC估算策略研究.天津大学学位论文,2006,32-34.
[94]夏超英,张术,孙宏涛.基于推广卡尔曼滤波算法的SOC估算策略[J].电源技术,2007,131(5):414-4
[2]慧琪.基于CAN总线的锂离子动力电池组管理系统[J].机电工程技术,2007,36(1):81-83
[3]贺本林.锂离子电池的新研究[D].兰州大学学位论文,2007.5:4-6
[4]李久芳.电动汽车镍氢电池剩余容量的测试研究[D].武汉理工大学学位论文,2004,5-7
[5]潘靖.锂电池智能管理系统[D].浙江大学硕士学位论文, 2004.3:4-5
[6]廖晓军,何莉萍,钟志华等.电池管理系统国内外现状及其未来发展趋势[J].汽车工程,2006,28(10):961-964
[7]刘均.动力电源管理系统设计与实现[D].哈尔滨工业大学学位论文,2004.6:5-8
[8]乔国艳.电动汽车电池管理系统的研究与设计[D].武汉理工大学硕士论文,2006.4:3-5
[9]刘志勇.电动汽车—中国汽车工业发展的必由之路[J].装备制造技,2009.(4):111-112
[10]宋德良.新排放法规对我国汽车及相关产业的挑战[J].上海汽车,2005,(5):30-32
[11]聂济宇.电动汽车非平稳工况的电源管理系统研究[D].西安交通大学硕士学位论文,2004.3:5-6
[12]张彦琴.混合动力车辆电池性能及其管理系统研究[D].北京工业大学博士论文,2006.9:17-18
[13]马建新,李青松,龚元明等.基于CAN总线的电动汽车蓄电池管理系统[J].机电一体化,2004,5:62-66
[14] Szumanowski,Y.Chang.Battery Management System Based on Battery Nonlinear Dynamics Modeling. IEEE Transactions on Vehicular Technology, 2008, No.3:124-127
[15]王林涛,陈德荣.锂离子电池均衡充电的设计[J].电源技术,2007,73(9):72-73
[16]雷娟,蒋新华,解晶莹.锂离子电池组均衡电路的发展现状[J].电池,2007,37(1) :62-63.
[17] Hande A,Stuart T A,A selective equalizer for Ni-MH batteries[J].J Power Sources,2004,138(1-2):327-339
[18]赵剑.电动汽车蓄电池剩余电量预测方法的研究[D].大连理工大学学位论文,2006,12:3-4
[19]吴友宇,尹叶舟.基于以CAN总线的分布式动力电池管理系统[J].汽车工程.20 04,26(5)::52-54.
[20] Chenghui Ca.State of charge estimation of high power NI-M H rechargeable batte -ry with artificle neural network[C]. Procceedings of the 9th Inetmational Confernceon Neural information Processing .2002. VOL.2:89-93.
[21]李贵海.电池SOC估算策略研究[D].浙江大学硕士学位论文,2006,8:6-7.
[22]邵海岳等.电动汽车用NIMH电池建模及基于状态空间的SOC预测方法[J].汽车工程,2004,26(5):534-537.
[23]美国先进电池联合会(USABC).电动汽车电池实验手册(英文).2001,32-34
[24]麻友良,陈全世,齐占宁.电动汽车用电池SOC定义与检测方法[J].清华大学学报(自然科学版),2001,41(11):453-457
[25]林成涛,王军,平陈全世.电动汽车SOC估计方法原理与应用[J].电池,2004,34(5):376-378.
[26]赵慧勇.车载镍氢电池管理系统研究现状与发展[J].湖北汽车工业学院学报,2004,18(3):1-4.
[27] JaeguIL,SoonjaeL,Namgoong.E“Dynamicst battery model with self- adaptive aging factor for EV and HEV application[C],Proceeding of the15th intermational electric vehicle symposium. San Franc -isco, Calif Electric Vehicle Association of the Americas:1998:57-59
[28]李革臣,古艳磊.电化学阻抗谱法预测锂电池荷电状态[J].电源技术,2008,32(9):599-602.
[29] Holger Blanke,OliverBohlen.Impedance measurements on lead-Cacid batteries for state-of-charge,state-of-health and cranking capability prognosis in electric and hybrid electric vehicles[J]. Journal of Power Sources. 2005.144:418-425
[30]赵徐成,张磊,黄卫星.基于动态电子负载的航空蓄电池内阻与容量关系[J].电源技术,2006,130(2):149-151.
[31] IRYN A,WILLiam R,ERBITS KIY, Battery open-circuit voltage estimation by a method of statistical analysis[J]. Journalof Power Sources 2006,159:1484–1487
[32] V.Pop, H.J.Bergveld. Modeling Battery Behavior for Accurate State-of-Charge Indication[J]. Journal of TheElectroc hemical Society, 2006.153:2013- 2022
[33] H.J. Bergveld, W.S. Kruijt, P.H.L. Notten, in Battery Management Systems Design by Modelling[M], Philips Research Book Series, Kluwer Academic Publishers,2002. vol. 1:48-51
[34]林成涛,王军平,王燕超.用改进的安时计量法估计电动汽车动力电池SOC[J].清华大学学报(自然科学版).2006,46(2):247-251.
[35]刘帅,宁武,王宏利.蓄电池电量监测新技术[J].辽宁工学院学报,2005,35(5):92-295
[36] POP V. Accuracy analysis Of the State-of Charge and remaining run-time determi -nation for lithium-ion batterie[J]. measurement,2008, 10:1016-1022
[37]王斯成,陈子平,杨军.蓄电池剩余容量(SOC)数学模型探讨和在线测试仪的开发[J].太阳能学报,2005,26(1):6-11
[38]李立伟,原明亭,包书哲.基于改进灰色模型的蓄电池剩余容量预测[J].电源技术,2006,130(12):1006-1008
[39] Il-Song Kim. The novel state of charge estimation method for lithium battery using sliding mode observer[J]. Journal of Power Sources. 2006,163:584–590
[40]焦慧敏,余群明.电动车用MH-Ni电池剩余电量的预测研究[J].计算机仿真,2006,23(3):211-214
[41]裴晟,陈全世,林成涛.基于支持向量回归的电池SOC估计方法研究[J].电源技术,2007,31(3):242-244
[42]李革臣,江海,王海英.基于模糊神经网络的电池剩余电量计算模型[J].测试技术学报,2007,21(5)::405-409.
[43] Pritpal Singh, Ramana Vinjamuri , Xiquan Wang. Fuzzy logic modeling of EIS measurements on lithium-ion batteries[J]. Electrochimica Acta . 2006,51:1673–1679
[44]吴红杰,齐铂金,郑敏信等.基于Kalman滤波的镍氢动力电池SOC估算方法[J].北京航空航天大学学报,2007,33(8):945-948.
[45]乐浪,李革臣,朱磊.卡尔曼滤波在电池检测中的应用[J].电源技术,2006,130(2):152-154.
[46] JAEMOON LE,OANYONG N,B.H CHO. Li-ion battery soc estimation method based on the reduced order extended Kalman filtering [J].Journal of PowerSources 2007,17:49–15
[47] Oanyong Nam; B.H. Cho. Li-ion battery SOC estimation method based on the reduced order extended Kalman filtering[J]. Journal of Power Sources; 2007, 174(1):9-15
[48] MorioK ,K azuhiroH ,AnilP Battery SOC and distance to empty of the Honda E VPlus[C].Proceedings of the14th Intenrational Electric Vehicle Symposium. San Franc -isco, Calif Electric Vehicle Association of the Americas:1997:156-159
[49]胡任,韩赞东,王克争.基于BP神经网络预测静置电池的剩余电量[J].电池,2006,36(1):58-59.
[50]齐智,吴锋,陈实.利用人工神经网络预测电池SOC的研究[J].电源技术,2005,29(5):325-328
[51]雷肖,陈清泉,刘开培.电动车电池SOC估计的径向基函数神经网络方法.电工技术学报,2008,23(5):81-87.
[52]陶兴华,陈彪.模糊逻辑与神经网络的蓄电池容量预测[J].电源技术,2004,28(9):578-581
[53] G.Plett.Extended Kalman Filtering for battery management systems of LiPB-based HEV battery packs Part2.Modeling and identificat ion[J].Journal of Power Sources, 2004,134:262-276.
[54] G.Plett.Extended Kalman Filtering for battery management systems of LiPB-based HEV battery packs[J]. Part 1. Background. J. Power Sour,2004,134(2):252-26
[55] Amir Vasebi ,Maral Partovibakhsh, S. Mohammad Taghi Bathaee. A novel combined battery model for state-of-charge estimation in lead-acid batteries based on extended Kalman filter for hybrid electric vehicle applications[J]. Journal of Power Sources.2007, 174:30–40
[56]戴海峰,魏学哲等.基于扩展卡尔曼滤波算法的燃料电池车用锂离子动力电池荷电状态估计[J].机械工程学报,2007,143(2):92-95.
[57]王贵明.电动车动力蓄电池实验建模研究[D].北方工业大学学位论文,2003:6.
[58]刘建国.燃料电池概述[J].物理,2004,33(2):79-83.
[59] D.A.J.Rand,P.T.Moseley等.阀控式铅酸蓄电池.北京:机械工业出版社.郭永榔等译,2007,1-2.
[60]张怀仁.镍氢电池电管理研究[D].国立中山大学学位论文,2005,6:14.
[61]唐有根.镍氢电池[M].北京:化学工业出版社,2007,11-13.
[62]胡仁法,浣上..镍镉电池的通用智能充电控制技术研究[C].中国控制与决策学术年会论文集,沈阳:东北大学出版社,2004,930-932.
[63]黄威.铅酸蓄电池组串联放电均衡控制实验研究[D].长沙理工大学学位论文,2005,4:6-7.
[64]秦爱辉.铅酸蓄电池充电系统研究[D].上海大学学位论文,2008,7-8.
[65]卢汉辉.蓄电池组充电管理系统关键技术的研究[D].上海交通大学学位论文,2007,2:6-7.
[66]郭炳昆.锂离子电池[M].湖南:中南大学出版社,2002:11-12.
[67]黄可龙.锂离子电池原理与关键技术[M].北京:化学工业出版社,2008,7-9.
[68]陈怡平.铅酸与锂离子蓄电池电量估计[D].国立中山大学论文,2007,6:5-7.
[69]栗宇深,汤敏贤,刘炤元．锂电池的原理与应用．电池工业，2004,8(4) :176-180.
[70]吴宇平.锂离子电池:应用与实践[M].北京:化学工业出版社,2004,2-3.
[71]王磊.锂电池充电器芯片的研究与设计[D].厦门大学学位论文,2007,1-2.
[72]李超..电动汽车用镍氢电池模型参数辨识和SOC估算研究[D].天津大学硕士学位论文.2007,2-3
[73]杨军,谢晶莹,王久林.化学电源测试原理与技术[M].北京:化学工业出版社,2006,7-11
[74]蒋新华.锂离子电池组应用电路研究.中国科学院上海微系统与信息技术研究所,2005,1-3.
[75]邓文莲.电动汽车动力电池的计算机管理[D].同济大学学位论文,2005,15-18.
[76]李冬梅.锂离子电池大电流放电分容测试系统的研究.华南理工大学学位论文,2007,7-9.
[77]冯华.电动汽车用电池管理系统的研制[D].北京交通大学学位论文,2007,11-12.
[78]裴锋,黄向东,罗玉涛.电动汽车动力电池变流放电特性与荷电状态实时估计[J].中国电机工程学报,2005,25(9):164-166.
[79]高怀.电动汽车电池管理系统的研究与设计[D].武汉理工大学学位论文,2007,11-12
[80]劳力..动力蓄电池管理系统SOC算法研究[D].北京交通大学学位论文,2007,24-25.
[81]赖世荣..智慧型锂离子电池残存电量之研究[D].国立中山大学学位论文,2004,37-41.
[82]毛宗强.燃料电池[M].北京:化学工业出版社,2005,16-19
[83] Butler J A V.Trans.Faraday Soc[M], Institute of Physical Chemistry, Czechoslovak Academy of Sciences, Prague 1924,19:734
[84] Tafel J Z.Physik.Chem[M], Springer-Verlag, Landolt-B?rnstein-Group IV Physical Chemistry, 1905,50:641
[85]黄文华,韩晓东,陈全世.电动汽车SOC估计算法与电池管理系统的研究[J].汽车工程,2007,29(3):198-201.
[86] Greg Welch. Gary Bishop. An Introduction to the Kalman Filter. Department of Computer Science University of North Carolina at Chapel Hill Chapel Hill, NC 27599-3175.2006.7
[87] R. E. KALMAN. A New Approach to Linear Filtering and Prediction Problems. ASME–Journal of Basic Engineering[J]. 1860.82 (Series D): 35-45.
[88]陈全世,林成涛.电动汽车用电池性能模型研究综述[J].汽车技术,2005,15(3):1-5.
[89]赵兴福.电动汽车蓄电池的建模与仿真研究[D].武汉理工大学硕士学位论文,2004,5-8.
[90] Shriram Santhanagopalan, Ralph E.White.Online estimation of the state of charge of a lithium ion cell. Journal of Power Sources. 2006,161:1346–1355
[91]卢居霄,林成涛,陈全世.三类常用电动汽车电池模型的比较研究[J].电源技术,2006,130(7)::535-538.
[92]王丽芳,胡运飞,廖承林.基于Thevenin改进模型的混合动力镍氢电池SOC估算研究[J].高技术通讯,2008,18(9):948-952.
[93]张术.电动汽车电池管理系统软件设计与SOC估算策略研究.天津大学学位论文,2006,32-34.
[94]夏超英,张术,孙宏涛.基于推广卡尔曼滤波算法的SOC估算策略[J].电源技术,2007,131(5):414-4