基于SVD-DAUKF算法的锂离子电池可用容量损失估计方法  

Estimation method of usable capacity loss for lithium ion battery based on SVD-DAUKF algorithm

作　　者：吴雨颢 仇胜世 王书航 王若宇 孙金磊[1] WU Yuhao;QIU Shengshi;WANG Shuhang;WANG Ruoyu;SUN Jinlei(School of Automation,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China)

机构地区：[1]南京理工大学自动化学院,江苏南京210094

出　　处：《电源技术》2024年第9期1667-1675,共9页Chinese Journal of Power Sources

基　　金：国家自然科学基金(52377209);江苏省研究生科研与实践创新计划项目(KYCX24_0662)。

摘　　要：锂离子电池以高能量密度、高功率密度和长使用寿命的特点被广泛应用于储能系统中。在长期运行状态下,可用容量的准确估计是储能系统参与电力调节的关键。为了解决这一问题,提出了一种基于奇异值分解的双自适应无迹卡尔曼滤波算法(singular value decomposition-double adaptive unscented Kalman filter,SVD-DAUKF)的锂离子电池可用容量损失估计方法。构建了考虑老化的电池可用容量表达式;利用SVD-DAUKF算法结合等效电路模型,进行模型参数辨识和电池荷电状态估计;结合参数辨识结果和可用容量定义,在1 C下进行可用容量损失估计结果的验证,可用容量损失估计误差低于4%。Lithium ion batteries are widely used in energy storage systems with high energy density,high power density and long service life.The accurate estimation of the usable capacity in the longterm operation state is the key for the energy storage system to participate in power regulation.In order to solve this problem,this paper proposes a method for estimating the usable capacity loss of lithium ion batteries based on Singular Value Decomposition-Double Adaptive Unscented Kalman Fil‐ter(SVD-DAUKF)algorithm,which firstly constructs the expression of battery usable capacity con‐sidering aging,and then uses the SVD-DAUKF algorithm combined with the equivalent circuit model to identify the model parameters and estimate the state of charge.Finally,combined with the param‐eter identification results and the definition of usable capacity,the estimation results of usable capac‐ity loss are verified at 1 C,and the estimation error of usable capacity loss is less than 4%.

关 键 词：锂离子电池 SVD-DAUKF算法 容量损失 

分 类 号：TM912[电气工程—电力电子与电力传动]