西安交通大学机械工程学院,西安,710049
网络首发:2017-07-10,
纸质出版:2017
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鲁伟, 续丹, 杨晴霞, 等. 锂电池分数阶建模与荷电状态研究[J]. 西安交通大学学报, 2017,51(7):124-129.
Fractional Model and State-of-Charge of Lithium Battery[J]. 2017, 51(7): 124-129.
鲁伟, 续丹, 杨晴霞, 等. 锂电池分数阶建模与荷电状态研究[J]. 西安交通大学学报, 2017,51(7):124-129. DOI: 10.7652/xjtuxb201707018.
Fractional Model and State-of-Charge of Lithium Battery[J]. 2017, 51(7): 124-129. DOI: 10.7652/xjtuxb201707018.
针对锂电池荷电状态估计不准确的问题
在对不同荷电状态的锂电池电化学阻抗谱进行了分析的基础上
利用分数阶建模思想建立了分数阶阻抗模型
并设计出一种分数阶卡尔曼滤波器
同时利用混合动力脉冲能力实验对建立的分数阶模型进行了参数辨识
从而实现了锂电池荷电状态的估算。实验及仿真结果表明:所设计的分数阶阻抗模型与分数阶卡尔曼滤波器能准确地描述锂电池的特性
使得荷电状态估算精度得以提高; 在城市道路循环工况下
锂电池的电压追踪误差可以稳定在0.05 V之内
在初始荷电状态未知的条件下
电池的荷电状态估计误差可以稳定在±1%。
Focusing on the inaccuracy of state-of-charge estimation of lithium battery
the electrochemical impedance spectroscopy of different state-of-charge stages of lithium battery is analyzed
and a fractional impedance model and a fractional Kalman filter are then proposed following the fractional modeling idea. The parameters of the model are identified in the hybrid pulse power characteristic(HPPC)test
and the state-of-charge estimation of lithium battery is accomplished by fractional Kalman filter. The result shows that the working voltage error is below 0.05 V and the estimation of state-of-charge error is below ±1%
thus the model is accurate enough to describe the characteristic of lithium battery and the fractional Kalman filter improves the accuracy of state-of-charge estimation of lithium battery.
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