一种锂离子电池荷电状态估计与功率预测方法

doi:10.19595/j.cnki.1000-6753.tces.160557

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Abstract In order to estimate the state of charge (SOC) of lithium-ion battery precisely and predict the actual maximum charge/discharge power of the battery,a second-order RC hysteresis model was established based on the hysteresis phenomena which appeared during the charge-discharge process.The H∞ filter algorithm was used to estimate SOC,which avoided the error caused by the statistical characteristics of noise.This method greatly reduces the model error and algorithm error,and improves the robustness of parameter estimation.Regard the battery voltage,current and the estimation of SOC as constraint conditions to predict the actual maximum charge-discharge power of the lithium-ion battery.Compared with the hybrid pulse power characterization (HPPC) method,the pulse charge-discharge experiments showed that the method proposed had higher accuracy in estimating the battery power.

Key words： Lithium-ion battery battery model state of change state of power

Received: 26 April 2016 Published: 18 August 2017

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TM911

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	Cheng Ze
	Sun Xingmian
	Cheng Silu

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Cheng Ze,Sun Xingmian,Cheng Silu. Method for Estimation of State of Charge and Power Prediction of Lithium-Ion Battery[J]. Transactions of China Electrotechnical Society, 2017, 32(15): 180-189.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.160557 OR https://dgjsxb.ces-transaction.com/EN/Y2017/V32/I15/180

[1] Joo G K,Byungrak S,el al.A review of lithium and non-lithium based solid state batteries[J].Journal of Power Sources,2015,282(15):299-322.
[2] Chen Xiaopeng,Shen Weixiang,Cao Zhenwei,et al.Adaptive gain sliding mode observer for state of charge estimation based on combined battery equivalent circuit model[J].Computers & Chemical Engineering,2014,64(18):114-123.
[3] Dai Haifeng,Guo Pingjing,Wei Xuezhe,et al.ANFIS (adaptive neuro-fuzzy inference system) based online SOC (State of Charge) correction considering cell divergence for the EV (electric vehicle) traction batteries[J].Energy,2015,80:350-360.
[4] 连湛伟,石欣,克潇,等.电动汽车充换电站动力电池全寿命周期在线检测管理系统[J].电力系统保护与控制,2014,42(12):137-142.
Lian Zhanwei,Shi Xin,Ke Xiao,et al.The whole life cycle on-line detection and management of system of power battery in the electric vehicle charging and exchanging station[J].Power System Protection and Control,2014,42(12):137-142.
[5] 于海芳,逯仁贵,朱春波,等.基于安时法的镍氢电池SOC估计误差校正[J].电工技术学报,2012,27(6):12-18.
Yu Haifang,Lu Rengui,Zhu Chunbo,et al.State of charge estimation calibration for Ni-MH battery based on ampere-hour method[J].Transactions of China Electrotechnical Society,2012,27(6):12-18.
[6] Weng Caihao,Sun Jing,Peng Huei.A unified open-circuit-voltage model of lithium-ion batteries for state-of-charge estimation and state-of-health monitoring[J].Journal of Power Sources,2014,258(14):228-237.
[7] 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,Chen Qingquan,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.
[8] Kalman R E.A new approach to linear filtering and prediction problems[J].Journal of basic Engineering,1960,82(1):35-45.
[9] 胡益,王晓茹,李鹏,等.静止同步串联补偿器(SSSC)的非线性鲁棒H∞控制策略研究[J].电力系统保护与控制,2015,43(7):30-36.
Hu Yi,Wang Xiaoru,Li Peng,et al.Nonlinear robust strategy static synchronous series compensator (SSSC) of H∞ control[J].Power System Protection and Control,2015,43(7):30-36.
[10]Gholizadeh M,Salmasi F R.Estimation of state of charge,unknown nonlinearities,and state of health of a lithium-ion battery based on a comprehensive unobservable model[J].IEEE Transactions on Industrial Electronics,2014,61(3):1335-1344.
[11]赵又群,周晓凤,刘英杰.基于扩展卡尔曼粒子滤波算法的锂电池 SOC 估计[J].中国机械工程,2015,26(3):394-397.
Zhao Youqun,Zhou Xiaofeng,Liu Yingjie.SOC estimation for Li-ion battery based on extended Kalman particile[J].China Mechanical Engineering,2015,26(3):394-397.
[12]刘金枝,杨鹏,李练兵.一种基于能量建模的锂离子电池电量估算方法[J].电工技术学报,2015,30(13):100-107.
Liu Jinzhi,Yang Peng,Li Lianbing.A method to estimate the capacity of the lithium-ion battery based on energy model[J].Transactions of China Electrotechnical Society,2015,30(13):100-107.
[13]赵淑红,吴锋,王子冬,等.动力电池功率密度性能测试评价方法的比较研究[J].兵工学报,2009,30(6):764-768.
Zhao Shuhong,Wu Feng,Wang Zidong,et al.Study on the different test methods for power density of power batteries[J].Acta Armamentarii,2009,30(6):764-768.
[14]刘莎,卢世刚,庞静.锂离子动力电池脉冲功率特性的研究[J].电源技术,2009,33(4):276-279.
Liu Sha,Lu Shigang,Pang Jing.Study on pulse power characteristics of lithium ion power battery[J].Chinese Journal of Power Sources,2009,33(4):276-279.
[15]Dees D,Gunen E,Abraham D,et al.Electrochemical modeling of lithium-ion positive electrodes during hybrid pulse power characterization tests[J].Journal of the Electrochemical Society,2008,155(8):A603-A613.
[16]孙丙香,姜久春,韩智强,等.基于不同衰退路径下的锂离子动力电池低温应力差异性[J].电工技术学报,2016,31(10):159-167.
Sun Bingxiang,Jiang Jiuchun,Han Zhiqiang,et al.The lithium-ion battery low temperature stress based on different degradation paths[J].Transactions of China Electrotechnical Society,2016,31(10):159-167.
[17]Fleischer C,Waag W,Heyn H M,et al.On-line adaptive battery impedance parameter and state estimation considering physical principles in reduced order equivalent circuit battery models:Part 1.Requirements,critical review of methods and modeling[J].Journal of Power Sources,2014,260(15):276-291.
[18]孙丙香,高科,姜久春,等.基于ANFIS和减法聚类的动力电池放电峰值功率预测[J].电工技术学报,2015,30(4):272-280.
Sun Bingxiang,Gao Ke,Jiang Jiuchun,et al.Research on discharge peak power prediction of battery based on ANFIS and subtraction clustering[J].Transactions of China Electrotechnical Society,2015,30(4):272-280.
[19]陈息坤,孙冬,陈小虎.锂离子电池建模及其荷电状态鲁棒估计[J].电工技术学报,2015,30(15):141-147.
Chen Xikun,Sun Dong,Chen Xiaohu.Modeling and state of charge robust estimation for lithium-ion batteries[J].Transactions of China Electrotechnical Society,2015,30(15):141-147.
[20]马丽萍,夏保佳.混合电动车用动力MH-Ni电池的研究现状与发展[J].电源技术,2003,27(增刊1):245-249.
Ma Liping,Xia Baojia.State-of-art of R & D of power Ni-MH battery for hybrid electric vehicle[J].Chinese Journal of Power Sources,2003,27(S1):245-249.
[21]Plett G L.High-performance battery-pack power estimation using a dynamic cell model[J].IEEE Transactions on Vehicular Technology,2004,53(5):1586-1593.
[22]刘艳莉,戴胜,程泽,等.基于有限差分扩展卡尔曼滤波的锂离子电池SOC估计[J].电工技术学报,2014,29(1):221-228.
Liu Yanli,Dai Sheng,Cheng Ze,et al.Estimation of state of charge of lithium-ion battery based on finite difference extended Kalman filter[J].Transactions of China Electrotechnical Society,2014,29(1):221-228.
[23]岳晓奎,袁建平.H∞滤波算法及其在GPS/SINS组合导航系统中的应用[J].航空学报,2001,22(4):366-368.
Yue Xiaokui,Yuan Jianping.H∞ filtering algorithm and its application in GPS/SINS integrated navigation system[J].Acta Aeronautica ET Astronautica Sinica,2001,22(4):366-368.
[24]胡再刚.基于H∞的传递对准方法研究[D].哈尔滨:哈尔滨工程大学,2007.
[25]秦永元.卡尔曼滤波与组合导航原理[M].西安:西北工业大学出版社,1998.
[26]秦琴,侯明善,杨常伟.自调节鲁棒H∞滤波目标机动估计[J].电光与控制,2007,14(2):30-33.
Qin Qin,Hou Mingshan,Yang Changwei.Target maneuvering estimations using H∞ filter and self-tuning second-order Markov process model[J].Electronics Optics & Control,2007,14(2):30-33.