基于系统辨识的电化学超级电容器建模

各种不同类型电化学超级电容器的工作机理有较大区别,为克服机理分析法不适合机理复杂系统的建模和通用性差的缺点,提出一种基于系统辨识方法建立的电化学超级电容器模型。首先计算确定辨识实验数据的采样周期和长度,并采用小波分析对其进行滤波处理;针对模型结构辨识问题,利用行列式比定阶法确定模型阶次,然后在此基础上辨识模型参数;最后对模型进行仿真分析和验证。结果表明,文中建模方法可行有效,所建立的模型可以准确描述超级电容器的特性,同时待辨识数据经过小波滤波处理后可以有效提高模型精度。

Modeling of Electrochemical Supercapacitor Based on System Identification

Because there are great differences between different kinds of electrochemical supercapacitor’s working principles,the mechanism analysis method is not suitable to model the electrochemical supercapacitor due to its poor generality.In this paper,a new model of electrochemical supercapacitor based on system identification was presented.Firstly,the sampling period and length of the experimental data were calculated and wavelet analysis was used to filter the data.Secondly,the determinant ratio was adopted to determine the model’s order.Then the parameters of the model were identified.Finally,the model was simulated and verified.The experimental and simulated results prove that the modeling method is feasible and effective and the model presented can depict the characteristics of supercapacitor exactly.In addition,the filtered data can greatly improve the precision of the model.