恒流
电池(电)
常量(计算机编程)
健康状况
电压
锂离子电池
时间常数
电阻器
均方根
电感器
波形
等效电路
控制理论(社会学)
电气工程
计算机科学
电子工程
工程类
功率(物理)
物理
人工智能
程序设计语言
量子力学
控制(管理)
作者
Jufeng Yang,Yingfeng Cai,Chris Mi
出处
期刊:IEEE Transactions on Transportation Electrification
日期:2021-11-08
卷期号:8 (2): 2070-2079
被引量:27
标识
DOI:10.1109/tte.2021.3125932
摘要
State-of-health (SoH) is one of the critical battery states that must be estimated and closely monitored by the on- board battery management system in electric vehicles (EVs). In this study, the battery SoH, especially the capacity fade, is calculated based on the decoupled characteristic of the charging current under the constant-voltage (CV) scenario. First, a dynamic-decoupled parameter identification method is proposed to extract the parameters of the simplified second-order resistor–inductor ( RL ) network-based equivalent circuit model (ECM), developed by the authors. Second, the dynamic characteristics of the decoupled CV charging currents at different aging states are qualitatively investigated, and the corresponding time constant is selected as a feature-of-interest (FoI) to reflect the battery capacity degradation. Third, the aging data based on two types of lithium-ion batteries are employed to evaluate the performance of the proposed method. Verification results demonstrate that the proposed parameter identification method yields a reduced computational cost with a satisfactory fitting performance, compared to the conventional methods. The proposed parameterization method and the selected FoI guarantee the root-mean-square errors of the estimated SoH less than 2%, and the comparative results further validate the superiority of the selected FoI in terms of the SoH estimation accuracy.
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