Lithium-ion battery SOC estimation based on robust H∞ filter
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摘要: 针对锂离子电池温度影响模型参数，进而导致SOC估计不准确的问题，本文提出了基于鲁棒H∞滤波的SOC准确估计方法。首先，以二阶Thevenin等效电路模型做为锂离子电池基础模型。并将温度对电池模型参数的影响建模为标称电阻值和电池总容量的加性变量，视温度变化为系统的外部扰动。其次，采用滑动线性法对电池模型进行线性化；并在此基础上运用线性矩阵不等式技术设计了对SOC进行估计的鲁棒H∞滤波器。最后，分别采用脉冲放电电流激励和实验数据电流激励，并将SOC的估计结果与kalman滤波对SOC的估计结果进行对比，其结果表明针对SOC估计所设计的鲁棒H∞滤波器能够实现对SOC的准确跟踪，同时对外部扰动具有较好的鲁棒性。Abstract: In this paper, an accurate SOC estimation method based on a robust H∞ filter is proposed, aiming at the problem that lithium-ion battery temperature affects model parameters, which leads to inaccurate SOC estimation,. Firstly, take the second-order Thevenin equivalent circuit model as the basic model of the lithium-ion battery. The influence of temperature on battery model parameters is modeled as an additive variable of the nominal resistance value and the total battery capacity, and the temperature change is regarded as an external disturbance of the system. After that, the sliding linear method is used to linearize its model; on this basis, a robust H∞ filter for SOC estimation is designed using linear matrix inequality technology. Finally, the pulse discharge current excitation and experimental data current excitation are used respectively, and the estimation result of SOC is compared with the estimation result of Kalman filter, which shows that the robust H∞ filter designed for SOC estimation can realize track SOC accurately, at the same time, it has good robustness to external disturbances.
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Key words:
- lithium-ion battery /
- SOC estimation /
- Model parameter perturbation /
- Model linearization /
- H∞ filter
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