Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach
Evaluation of Lithium-Ion Battery Equivalent Circuit Models for State of Charge Estimation by an Experimental Approach
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DOI：
10.3390/en4040582
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发表时间：
2011-04-01
期刊：
影响因子：
3.2
通讯作者：
Fan, Jinxin
中科院分区：
文献类型：
--
作者：
He, Hongwen;Xiong, Rui;Fan, Jinxin
为了提高锂离子电池在电动汽车（EV）应用中的使用，本文提出了不同的等效电路模型的评估和比较。在分析传统的锂离子电池等效电路模型Rint、RC、戴维南（Thevenin）和PNGV模型的基础上，提出了一种改进的戴维南模型--双极化（DP）模型，通过增加一个RC来分别模拟电化学极化和浓差极化。模型参数的识别与遗传算法，这是用来找到最佳的时间常数的模型，并从混合脉冲功率特性（HPPC）测试的LiMn 2 O 4电池模块的实验数据。从动态性能和荷电状态估计的角度对这五种模型进行了评价。通过进行动态应力测试（DST）获得五个模型的动态性能，并且通过进行联邦城市驾驶时间表（FUDS）实验来确定使用鲁棒扩展卡尔曼滤波（REKF）方法的SoC估计的准确性。通过比较，DP模型具有最好的动态性能，并提供最准确的SoC估计。最后，根据基于DP模型的REKF方法对SoC估计的准确性，研究了不同SoC初始值的敏感性。很明显，由SoC初始值引起的误差显著减小，并且真实SoC在可接受的误差内收敛。
To improve the use of lithium-ion batteries in electric vehicle (EV) applications, evaluations and comparisons of different equivalent circuit models are presented in this paper. Based on an analysis of the traditional lithium-ion battery equivalent circuit models such as the Rint, RC, Thevenin and PNGV models, an improved Thevenin model, named dual polarization (DP) model, is put forward by adding an extra RC to simulate the electrochemical polarization and concentration polarization separately. The model parameters are identified with a genetic algorithm, which is used to find the optimal time constant of the model, and the experimental data from a Hybrid Pulse Power Characterization (HPPC) test on a LiMn2O4 battery module. Evaluations on the five models are carried out from the point of view of the dynamic performance and the state of charge (SoC) estimation. The dynamic performances of the five models are obtained by conducting the Dynamic Stress Test (DST) and the accuracy of SoC estimation with the Robust Extended Kalman Filter (REKF) approach is determined by performing a Federal Urban Driving Schedules (FUDS) experiment. By comparison, the DP model has the best dynamic performance and provides the most accurate SoC estimation. Finally, sensitivity of the different SoC initial values is investigated based on the accuracy of SoC estimation with the REKF approach based on the DP model. It is clear that the errors resulting from the SoC initial value are significantly reduced and the true SoC is convergent within an acceptable error.