摘要
电池的荷电状态(state-of-charge,SOC)估算和电池均衡作为电池管理系统(battery management system,BMS)的核心功能,对电池的一致性和使用寿命、安全等至关重要。在电池的工作期间,温度直接影响了电池的可用容量和放电特性,从而加剧了SOC的估算误差。因此,考虑了温度对电池的影响,对SOC估算方法进行了改进,并利用主被动均衡改善了单体一致性问题。首先,通过建立电池的热特性模型对电池的内部温度进行估计,将温度估计结果对扩展卡尔曼滤波(extended Kalman filter,EKF)算法进行了改进,再使用该算法进行SOC估算。并分别在城市道路循环工况(urban dynamometer driving schedule,UDDS)、动态应力测试(dynamic stress test,DST)、混合脉冲功率特性(hybrid pulse power characterization,HPPC)工况下验证了改进算法对提高SOC估算精度的有效性。其次,以更高精度的SOC估算结果作为变量,提出一种主被动均衡电路并合理设计了均衡策略。最后,在仿真验证下,改进的EKF算法显著提高了SOC的估算精度,并通过主被动均衡实现了DST工况下一组SOC极差为13%的六节单体电池之间的快速均衡。结果表明,改进的EKF算法能有效降低温度带来的SOC估算误差,改善电池单体间的不一致性问题。
The battery’s state-of-charge(SOC)estimation and equalization are the core functions of the battery management system(BMS).They are critical for the battery’s consistency,service life and safety.During the discharge of the battery,the temperature directly affects the available capacity and discharge characteristics of the battery,thus exacerbating the error in SOC estimation.The effect of temperature variation on battery SOC estimation was quantified,and the cell consistency problem was improved using active-passive equalization method.Firstly,a thermal characteristic model of the battery was established to estimate the internal temperature of the battery,and the estimated temperature was used to improve the extended Kalman filter(EKF)algorithm for estimating the SOC.The effectiveness of the improved algorithm for improving the accuracy of SOC estimation was verified under the urban dynamometer driving schedule(UDDS),dynamic stress test(DST),and hybrid pulse power characterization(HPPC)working conditions,respectively.Secondly,an active-passive equalization circuit and equalization strategy with higher accuracy SOC estimation results as variables were proposed.Finally,under the simulation verification,the SOC estimation accuracy was significantly improved by the improved EKF algorithm.Under the DST condition,the equalization between the six cells with a SOC-range of 13%was quickly completed by the active-passive equalization method.The results show that the SOC estimation error caused by temperature is effectively reduced by the improved method,and the inconsistency between single cells is also reduced.
作者
孙正
李军
李虎林
SUN Zheng;LI Jun;LI Hu-lin(School of Mechanical,Electrical and Vehicle Engineering,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《科学技术与工程》
北大核心
2022年第33期14767-14778,共12页
Science Technology and Engineering
基金
国家自然科学基金(51305472)
重庆市研究生联合培养基地项目(JDLHPYJD2018003)。
关键词
电池热特性模型
扩展卡尔曼滤波算法
SOC估算
主被动均衡
battery thermal characteristic model
extended Kalman filter algorithm
SOC estimation
active and passive equalization