摘要
采用Fisher信息矩阵进行参数可辨识性分析,解决了参数的辨识问题,进而提出了基于简化电化学机理模型SP2D(simple pseudo-two-dimensional)的SOC(电池电量)在线估计方法。实验表明,该SOC估计方法较基于等效电路模型(一阶RC模型)的SOC估计方法,可将SOC估计的平均误差减小近30%,而在电池放电中后期更可减小达60%,有效解决了在电池全工作范围内的SOC高精度估计问题。
The Fisher information matrix was adopted to identify the parameters of a lithium-ion battery, and an online SOC(state of charge) estimation method was proposed based on the SP2D (simple pseudotwo- dimensional) model. Compared with the results of the equivalent circuit model, the experiment verifies that the proposed SOC estimation method has higher precision. Effectively solving the problem of SOC high accuracy estimation in the whole range of SOC, the average error of SOC can be reduced by nearly 30%, and by 60% in the later stage of battery discharge.
作者
邓昊
杨林
邓忠伟
李冬冬
杨洋
蔡亦山
羌嘉曦
DENG Hao;YANG Lin;DENG Zhongwei;LI Dongdong;YANG Yang;CAI Yishan;QIANG Jiaxi(School of Mechanical Engineering,Shanghai Jiao Tong University,Shanghai 200240,China;Shanghai 01 Power Technology Co.,Ltd.,Shanghai 200240,China)
出处
《上海理工大学学报》
CAS
北大核心
2018年第6期557-565,共9页
Journal of University of Shanghai For Science and Technology
基金
国家自然科学基金资助项目(51741707)
关键词
电化学模型
可辨识性分析
参数辨识
在线SOC估计
electrochemical model
identifiability analysis
parameter identification
online SOC(stateof charge) estimation