基于极化效应PNGV模型的动力锂电池SOC估算
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摘要
为提高锂电池荷电状态的估算精度及模拟锂离子电池实际充放电特性的准确性,本文通过改进现有的PNGV等效电路模型,在PNGV模型基础上,增加一节RC并联模块,使模型更好的反映电池的极化效应。同时,通过实验获取电池充放电特性,为卡尔曼滤波器提供精确的参数,并提出了电池的开路电压曲线模型,通过Matlab拟合验证满足精度要求。最后采用扩展卡尔曼滤波(extended kalmanfilter,EKF)算法对锂电池荷电状态(state of charge,SOC)进行估算,并与安时积分法进行比较。实验结果表明,估算最大误差不超过4.5%,平均不超过3%,提高了SOC的估算精度。该研究为电动汽车运行工况提供了理论依据。
Lithium-ion batteries are superior to other types of batteries in electric vehicle applications due to their safety,fast charging capability and long cycle life.In order to improve the estimation accuracy of the state of charge of the lithium battery and the accuracy of the model to simulate the actual charge and discharge characteristics of the lithium ion battery.Firstly,by improving the existing PNGV equivalent circuit mathematical model,based on the PNGV model,by adding an RC parallel module,the model can better reflect the polarization effect of the battery.Secondly,the charge and discharge characteristics of the battery are obtained through experiments to provide accurate parameters for the Kalman filter,and an open-circuit voltage curve model of the battery is proposed,and the accuracy is satisfied by the Matlab fitting verification.Finally,the EKF algorithm is used to estimate the SOC of the lithium battery and it is compared with the Ah integration method.The experimental verification verifies that the maximum error is less than 4.5%,and the average is less than3%.Experimental verification shows that the SOC estimation accuracy has been effectively improved.
Lithium-ion batteries are superior to other types of batteries in electric vehicle applications due to their safety,fast charging capability and long cycle life.In order to improve the estimation accuracy of the state of charge of the lithium battery and the accuracy of the model to simulate the actual charge and discharge characteristics of the lithium ion battery.Firstly,by improving the existing PNGV equivalent circuit mathematical model,based on the PNGV model,by adding an RC parallel module,the model can better reflect the polarization effect of the battery.Secondly,the charge and discharge characteristics of the battery are obtained through experiments to provide accurate parameters for the Kalman filter,and an open-circuit voltage curve model of the battery is proposed,and the accuracy is satisfied by the Matlab fitting verification.Finally,the EKF algorithm is used to estimate the SOC of the lithium battery and it is compared with the Ah integration method.The experimental verification verifies that the maximum error is less than 4.5%,and the average is less than3%.Experimental verification shows that the SOC estimation accuracy has been effectively improved.
引文
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[2]汪世国.电动汽车电池管理系统(BMS)现状分析[J].汽车实用技术,2014(2):65-67.
[3]余奇.纯电动汽车动力电池荷电状态估计的研究[D].哈尔滨:哈尔滨工业大学,2016.
[4]卢杰祥.锂离子电池特性建模与SOC估算研究[D].广州:华南理工大学,2012.
[5]李莉,朱珺.无偏转换卡尔曼滤波在雷达目标跟踪中的应用[J].电子测量技术,2011,34(4):30-32.
[6]李德东,王振臣,郭小星.基于模糊卡尔曼滤波的HEV氢镍电池SOC估计[J].电源技术,2011,35(2):192-194.
[7]苗强.基于载荷重构的混合动力公交车能量管理策略优化研究[D].济南:山东大学,2017.
[8]张金龙,佟微,漆汉宏,等.平方根采样点卡尔曼滤波在磷酸铁锂电池组荷电状态估算中的应用[J].中国电机工程学报,2016,36(22):6246-6253.
[9]张利,张庆,常成,等.用于电动汽车SOC估计的等效电路模型研究[J].电子测量与仪器学报,2014(10):1161-1168.
[10]魏增福,董波,刘新天,等.锂电池动态系统Thevenin模型研究[J].电源技术,2016,40(2):291-293.
[11]Taheri P,Mansouri A,Yazdanpour M,et al.Theoretical analysis of potential and current distributions in planar electrodes of lithium-ion batteries[J].Electrochimica Acta,2014,133(133):197-208.
[12]杨帆,乔艳龙,甘德刚,等.不同充电模式对锂离子电池极化特性影响[J].电工技术学报,2017,32(12):171-178.
[13]李志农,覃章锋.基于降低极化电压磷酸铁锂电池充电方法研究[J].汽车技术,2017(11):24-29.
[14]白婷.锂离子电池间歇-正负脉冲优化充电方法研究[D].武汉:湖北工业大学,2014.
[15]谢祖荣,车勇,黄之初.基于Matlab的RLC二阶电路零输入响应的研究[J].武汉理工大学学报,2002,24(1):46-49.
[16]Fernández-Villaverde J,Gordon G,Guerrón-Quintana P,et al.Nonlinear adventures at the zero lower bound[J].Journal of Economic Dynamics&Control,2015,57(6):182-204.
[17]薛长虎,聂桂根,汪晶.扩展卡尔曼滤波与粒子滤波性能对比[J].测绘通报,2016(4):10-14.
[18]黄飞,钟家伟.泰勒公式及泰勒级数的应用[J].佳木斯大学学报:自然科学版,2016,34(6):1029-1032.
[19]Zhang C,Wang L Y,Li X,et al.Robust and adaptive estimation of state of charge for lithium-Ion batteries[J].IEEE Transactions on Industrial Electronics,2015,62(8):4948-4957.
[20]Fath K,Stengel J,Sprenger W,et al.A method for predicting the economic potential of(building-integrated)photovoltaics in urban areas based on hourly radiance simulations[J].Solar Energy,2015,116(4):357-370.