论文标题
使用moli方法鉴定锂离子细胞的最佳预测误差模型
Identification of optimal prediction error Thévenin models of Li-ion cells using the MOLI approach
论文作者
论文摘要
该报告提出了系统识别算法，以估计锂细胞的动力学模型。首先，研究了开路电压（OCV）对电荷状态（SOC）的依赖性。说明电池等效模型时，将电阻添加到电路中。排放数据分为假定内部电阻恒定的段，因此SOC是恒定的，因此，将LTI鉴定算法描述为用于估计每个段中的细胞模型。将Randles电路引入模型，以描述扩散过程。该模型包括所谓的Warburg阻抗，该阻抗是分数系统。讨论了这种阻抗，并通过有限的线性时间不变状态空间模型进行了近似。同样，在提出了简化的兰德尔电路之后，被陈述了一种识别算法，该算法估计了该模型的参数。 Thévenin模型作为Randles Circuit的替代方案。阐明了一种识别第一和第二阶模型的算法。使用一组实验集的数据讨论并比较了简化的Randles模型和所述的两个Thévenin模型及其各自识别算法的性能。
This report presents System Identification algorithms to estimate the dynamical model of Li-Oin cells. First the dependence of open circuit voltage (OCV) on the state of charge (SOC) is studied. thN battery equivalent model when a resistor is added to the circuit is stated. The discharge data is divided into segments where the internal resistance is assumed constant, and therefore SOC is constant, thence is described an LTI identification algorithm to be used to estimate the cell model in each segment. A Randles circuit is introduced to the model to describe the diffusion process. This model includes the so called Warburg impedance which is as fractional system. This impedance is discussed and it is approximatted by a finite order linear time invariant state-space model. Also, after presenting the simplified Randles circuit, is stated an identification algorithm that estimates the parameters of this model. The Thévenin model is presented as an alternative to the Randles circuit. An algorithm to identify a Thévenin model of 1st and 2nd order is enunciated. The performances of the simplified randles model and of the two Thévenin models models described and its respective identification algorithms, are discussed and compared using an experimental set of data.
