论文标题
伪2D锂离子电池电化学模型的结构可识别性
Structural Identifiability of a Pseudo-2D Li-ion Battery Electrochemical Model
论文作者
论文摘要
对快速充电和优化电池设计的需求不断增长，这引起了人们对锂离子电池电化学模型的重大兴趣。但是，对这些模型的估计参数值仍然是一个重大挑战。在本文中，将结构可识别性分析应用于伪2D锂离子电化学电池模型，该模型可以被视为基准Doyle-Fuller-Newman模型的线性化和分离形式。从对阻抗函数的检查，可以证明该模型是由21个参数唯一对电导参数的组合来唯一的参数，例如电导率和扩散系数。然后建立了参数估计问题的适当性，并建立了这些参数。通过识别可以从数据中唯一识别的参数集，该结果可能会导致对电池内部状态的更现实的预测。
Growing demand for fast charging and optimised battery designs is fuelling significant interest in electrochemical models of Li-ion batteries. However, estimating parameter values for these models remains a major challenge. In this paper, a structural identifiability analysis was applied to a pseudo-2D Li-ion electrochemical battery model that can be considered as a linearised and decoupled form of the benchmark Doyle-Fuller-Newman model. From an inspection of the impedance function, it was shown that this model is uniquely parametrised by 21 parameters, being combinations of the electrochemical parameters like the conductivities and diffusion coefficients. The well-posedness of the parameter estimation problem with these parameters was then established. This result could lead to more realistic predictions about the internal state of the battery by identifying the parameter set that can be uniquely identified from the data.
