Comparison of Nonlinear Filtering Methods for Estimating the State of Charge of Li4Ti5O12 Lithium-Ion Battery
Comparison of Nonlinear Filtering Methods for Estimating the State of Charge of Li4Ti5O12 Lithium-Ion Battery
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用于估算 Li4Ti5O12 锂离子电池充电状态的非线性滤波方法的比较
DOI：
10.1155/2015/485216
复制
发表时间：
2015-10
影响因子：
--
通讯作者：
He, Hongwen
中科院分区：
文献类型：
--
作者：
Gao, Jianping;He, Hongwen
准确的荷电状态估计对于锂离子电池的安全运行和防止过充过放具有重要意义。为了实现对Li4Ti5O12锂离子电池单元的可靠SoC估计，比较和评估了三种滤波方法。本研究的一个主要贡献是，一个通用的三步模型为基础的电池SoC估计方案已被提出。它包括电池数据测量、参数建模和基于模型的SoC估计的过程。与所提出的一般计划，多种类型的基于模型的SoC估计器已经开发和评估的电池管理系统的应用。详细比较了三种先进的自适应滤波技术，包括扩展卡尔曼滤波器，无迹卡尔曼滤波器，自适应扩展卡尔曼滤波器（AEKF），已实现与Li4Ti5O12锂离子电池。实验结果表明，基于模型的AEKF算法具有较好的估计精度和鲁棒性，尤其在SoC初始误差较大的情况下，估计的平均绝对误差在1%以内。
Accurate state of charge (SoC) estimation is of great significance for the lithium-ion battery to ensure its safety operation and to prevent it from overcharging or overdischarging. To achieve reliable SoC estimation for Li4Ti5O12 lithium-ion battery cell, three filtering methods have been compared and evaluated. A main contribution of this study is that a general three-step model-based battery SoC estimation scheme has been proposed. It includes the processes of battery data measurement, parametric modeling, and model-based SoC estimation. With the proposed general scheme, multiple types of model-based SoC estimators have been developed and evaluated for battery management system application. The detailed comparisons on three advanced adaptive filter techniques, which include extend Kalman filter, unscented Kalman filter, and adaptive extend Kalman filter (AEKF), have been implemented with a Li4Ti5O12 lithium-ion battery. The experimental results indicate that the proposed model-based SoC estimation approach with AEKF algorithm, which uses the covariance matching technique, performs well with good accuracy and robustness; the mean absolute error of the SoC estimation is within 1% especially with big SoC initial error.
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DOI：
10.1017/cbo9781139207249.009
发表时间：
2012
期刊：
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影响因子：
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通讯作者：
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影响因子：
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DOI：
10.1109/sap.1970.269992
发表时间：
1970-12
期刊：
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影响因子：
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作者：
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