Robust and Adaptive Estimation of State of Charge for Lithium-Ion Batteries
Robust and Adaptive Estimation of State of Charge for Lithium-Ion Batteries
复制标题
锂离子电池充电状态的鲁棒自适应估计
DOI：
10.1109/tie.2015.2403796
复制
发表时间：
2015-02
影响因子：
7.7
通讯作者：
Jiuchun Jiang
中科院分区：
文献类型：
--
作者：
Caiping Zhang;Le Yi Wang;Xue Li;Wen Chen;George G. Yin;Jiuchun Jiang
电池管理系统的可靠运行关键取决于对电池系统的荷电状态（SOC）和特征参数的准确估计。SOC估计采用必须对电池单元电化学特征、老化和操作条件的变化具有鲁棒性的模型。本文揭示了常用的SOC估计方案在提供SOC估计对模型不确定性的鲁棒性方面存在根本缺陷。为了提高SOC估计的准确性和鲁棒性，本文介绍了参数估计方法和自适应SOC估计设计。通过对参数变化对SOC估计精度的影响的详细审查，SOC开路电压映射被确定为必须准确建立的最关键的功能。辨识算法，并建立其收敛性。的识别算法和SOC估计方案的集成导致一个自适应SOC估计框架，是上级现有的方法，在提供更高的精度和鲁棒性。实验研究进行了验证算法。
The reliable operation of battery management systems depends critically on the accurate estimation of the state of charge (SOC) and characterizing parameters of a battery system. SOC estimation employs models that must be robust against variations in battery cell electrochemical features, aging, and operating conditions. This paper reveals that commonly used SOC estimation schemes are fundamentally flawed in providing the robustness of SOC estimation against model uncertainties. Parameter estimation methodologies and adaptive SOC estimation design are introduced in this paper to enhance SOC estimation accuracy and robustness. By a scrutiny of the impact of parameter variations on SOC estimation accuracy, the SOC-open-circuit-voltage mapping is identified to be the most critical function that must be accurately established. Identification algorithms are introduced, and their convergence properties are established. The integration of the identification algorithms and SOC estimation schemes lead to an adaptive SOC estimation framework that is superior over the existing methods in providing much improved accuracy and robustness. Experimental studies are conducted to validate the algorithms.
登录
查看更多内容
影响因子：
8.8
作者：
Mark Sitterly;L. Wang;G. Yin;Caisheng Wang
通讯作者：
Mark Sitterly;L. Wang;G. Yin;Caisheng Wang
影响因子：
7.7
作者：
M. Gholizadeh;F. R. Salmasi
通讯作者：
M. Gholizadeh;F. R. Salmasi
DOI：
10.1080/1448837x.2012.11464327
发表时间：
2012-01
影响因子：
--
作者：
Xiaopeng Chen;Weixiang Shen;Zhenwei Cao;Ajay Kapoor
通讯作者：
Xiaopeng Chen;Weixiang Shen;Zhenwei Cao;Ajay Kapoor
影响因子：
11.2
作者：
He, Hongwen;Xiong, Rui;Guo, Hongqiang
通讯作者：
Guo, Hongqiang
影响因子：
7.7
作者：
Shahriari, Mehrnoosh;Farrokhi, Mohammad
通讯作者：
Farrokhi, Mohammad