摘要
为了精准估计锂电池荷电状态(SOC),选用戴维南等效电路模型,通过分段线性化拟合OCV-SOC曲线,采用基于扩展卡尔曼滤波(EKF)及容量校准的SOC估计方法。建立电池状态空间方程,考虑电池老化因素,采用SOC估计值与安时积分结合的方法对总容量进行校准,并在美国联邦城市运行工况下进行仿真与实验验证。结果显示,方案所得的SOC估计误差在2.1%以内。
To accurately estimate the state of charge(SOC)of lithium battery,the Thevenin equivalent circuit model was selected,the OCV-SOC curve was fitted by piecewise linearization,and the SOC estimation method based on extended Kalman filter(EKF)and capacity calibration was adopted.The state space equation of the battery was established.Considering the aging factors of the battery,the total capacity was calibrated by the method of combining SOC estimation and ampere-hour integration.The simulation and experimental verification were carried out under the federal urban driving sechedule operating condition.The results show that the SOC estimation error of the proposed scheme is within 2.1%.
作者
彭香园
唐传雨
孙金磊
刘钊
PENG Xiangyuan;TANG Chuanyu;SUN Jinlei;LIU Zhao(School of Automation,Nanjing University of Science and Technology,Nanjing 210000,China)
出处
《电器与能效管理技术》
2020年第5期51-56,共6页
Electrical & Energy Management Technology
基金
江苏省重点研发计划(BE2019018)
江苏省研究生科研创新计划项目(SJKY19_0323)。
关键词
荷电状态
锂电池
戴维南等效电路模型
扩展卡尔曼滤波
容量校准
state of charge(SOC)
lithium batteries
Thevenin equivalent circuit model
extended Kalman filter(EKF)
capacity calibration
作者简介
彭香园(1999—),女,研究方向为电池管理技术;唐传雨(1995—),男,研究方向为电池状态估计技术和电池均衡技术;孙金磊(1985—),男,讲师,研究方向为电池管理技术。
