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基于自适应无迹卡尔曼滤波算法的锂离子动力电池状态估计

DOI: 10.13334/j.0258-8013.pcsee.2014.03.016, PP. 445-452

Keywords: 荷电状态,健康状态,自适应无迹卡尔曼滤波器,电动汽车,锂离子动力电池

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Abstract:

应用传统的无迹卡尔曼滤波(unscentedKalmanfilter,UKF)算法估计电动汽车锂离子动力电池核电状态(stateofcharge,SOC)时,常会出现由于电池模型参数不准确而造成估计误差增大的问题,该文采用了自适应无迹卡尔曼滤波(adaptiveunscentedKalmanfilter,AUKF)算法解决该问题。AUKF算法是一种循环迭代算法,可以实时估计电池模型中的欧姆内阻,提高电池模型准确性,从而提高电池SOC估计精度。另外,电池的欧姆内阻可以表征电池的健康状态(stateofhealth,SOH),因此还可以根据电池的欧姆内阻估计出电池的SOH。在设定工况下对电池做充放电实验,实验分析表明,与UKF相比,AUKF提高了电池SOC估计的精度,并能准确的估计出电池的欧姆内阻。

References

[1]  Alvin J S, Craig F, Pritpal S, et al.Determina-tion of state-of-charge and state-of-health of batteries by fuzzy logic methodology[J].Journal of Power Sources, 1999, 80(1-2):293-300.
[2]  戴海峰, 孙泽昌, 魏学哲.利用双卡尔曼滤波算法估计电动汽车用锉离子动力电池的内部状态[J].机械工程学报, 2009, 45(6):95-101.Dai Haifeng, Sun Zechang, Wei Xuezhe.Estimation of internal states of power lithium-ion batteries used on electric vehicles by dual extended Kalman filter [J].Journal of Mechanical Engineering, 2009, 45(6):95-101(in chinese).
[3]  Neeta K, Shalini C, Rekha G.Statistical modeling of SOH of an automotive battery for online indication[C]// Proceedings of IEEE 30th International Telecommunications Energy Conference.San Diego, USA:IEEE, 2008:1-7.
[4]  Alexander P, Matthias B, Árpád W, et al.Model-based distinction and quantification of capacity loss and rate capability fade in Li-ion batteries[J].Journal of Power Sources, 2010, 195(22):7634-7638.
[5]  全国汽车标准化技术委员会.QC/T 743-2006电动汽车用锂离子蓄电池[S].北京:中国计划出版社, 2006.National Technical Committee of Auto Standardization.QC/T 743-2006 Lithium-ion batteries for electric vehicles[S].Beijing:China Planning Press, 2006(in Chinese).
[6]  Plett G L.Extended kalman filtering for battery management systems of LiPB-based HEV battery packs part 1 background[J].Journal of Power Sources, 2004, 143(134):252-261.
[7]  Meissner E, Richter G.The challenge to the automotive battery industry:the battery has to become an increasingly integrated component within the vehicle electric power system[J].Journal of Power Sources, 2005, 144(2):438-460.
[8]  Ng K S, Moo C S, Chen Y P, et al.Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries[J].Applied Energy, 2009, 86(9):1506-1511.
[9]  Remmlinger J, Buchholz M, Meiler M, et al.State- of-health monitoring of lithium-ion batteries in electric vehicles by on-board internal resistance estimation [J].Journal of Power Sources, 2001, 196(12):5357-5363.
[10]  Aylor J H, Thieme A, Johnson B W.A battery state of charge indicator for electric wheelchairs[J].IEEE Trans.on Industrial Electronics, 1992, 39(5):398-409.
[11]  雷肖, 陈清泉, 刘开培, 等.电动车蓄电池荷电状态估计的支持向量机方法[J].中国电机工程学报, 2008, 28(18):114-118.Lei Xiao, Chen Qingquan, Liu Kaipei, et al.Support vector machine based SoC estimation for electric vehicles [J].Proceedings of the CSEE, 2008, 28(18):114-118(in Chinese).
[12]  雷肖, 陈清泉, 刘开培, 等.电动车电池SoC估计的径向基函数神经网络方法[J].电工技术学报, 2008, 23(5):81-87.Lei Xiao, Chan Chenquan, Liu Kaipei, et al.Radial- based-function neural network based SoC estimation for electric vehicles[J].Transactions of China Electrotechnical Society, 2008, 23(5):81-87(in Chinese).
[13]  裴锋, 黄向东, 罗玉涛, 等.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):164-168.Pei Feng, Huang Xiangdong, Luo Yutao, et al.Variable current discharge characteristics and SoC estimation of EV/HEV battery[J].Proceedings of the CSEE, 2005, 25(9):164-168(in chinese).
[14]  Plett G L.Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs part 2 modeling and identification[J].Journal of Power Sources, 2004, 143(134):262-276.
[15]  Plett G L.Extended Kalman filtering for battery management systems of LiPB-based HEV battery packs part 3 state and parameter estimation[J].Journal of Power Sources, 2004, 143(134):277-292.
[16]  Dai H, Wei X, Sun Z.Design and implementation of a UKF-based SOC estimator for LiMnO2 batteries used on electric vehicles[J].Przeglad Elektrotechniczny, 2012, 88(1):57-63.
[17]  Santhanagopalan S, White R E.State of charge estimation using an unscented filter for high power lithium ion cells[J].International Journal of Energy Research, 2010, 34(2):152-163.
[18]  Takeno K, Ichimura M, Takano K, et al.Quick testing of batteries in lithium-ion battery packs with impedance-measuring technology[J].Journal of Power Sources, 2004, 128(1):67-75.
[19]  Blanke H, Bohlen O, Buller S, et al.Impedance measurements on lead-acid 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(2):418-425.
[20]  Abrahama D P, Knuth J L, Dees D W, et al.Performance degradation of high-power lithium-ion cells- electrochemistry of harvested electrodes[J].Journal of Power Sources, 2007, 170(2):65-475.
[21]  Karden E, Buller S, De Doncker R D.A method for measurement and interpretation of impedance spectra for industrial batteries[J].Journal of Power Sources, 2000, 85(1):72-78.
[22]  Ramadass P, Haran B, White R, et al.Mathematical modeling of the capacity fade of Li-ion cells[J].Journal of Power Sources, 2003, 123(2):230-240.

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