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A Computationally Efficient Implementation of an Electrochemistry-Based Model for Lithium-Ion Batteries

机译:基于电化学的锂离子电池模型的计算有效实现

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Lithium-ion batteries are commonly employed in various applications owing to high energy density and long service life. Lithium-ion battery models are used for analysing batteries and enabling power control in applications. The Doyle-Fuller-Newman (DFN) model is a popular electrochemistry-based lithium-ion battery model which represents solid-state and electrolyte diffusion dynamics and accurately predicts the current/voltage response. However, implementation of the full DFN model requires significant computation time. This paper proposes a computationally efficient implementation of the full DFN battery model, which is convenient for real-time applications. The proposed implementation is based on spatial and temporal discretisation of the governing partial differential equations and a particular numerical method for solving the resulting discretised model equations, which is based on a damped Newton’s method. In a simulation study, the numerical efficiency of the proposed implementation is shown.
机译:由于高能量密度和长使用寿命,锂离子电池通常用于各种应用中。锂离子电池模型用于分析电池并在应用中实现功率控制。 Doyle-Fuller-Newman(DFN)模型是一种流行的基于电化学的锂离子电池模型,它代表固态和电解质扩散动力学,并准确预测电流/电压响应。但是,完整DFN模型的实现需要大量的计算时间。本文提出了一个完整的DFN电池模型的高效计算实现,这对于实时应用很方便。拟议的实现基于控制偏微分方程的空间和时间离散化,以及一种基于阻尼牛顿法的用于求解所得离散模型方程的特定数值方法。在仿真研究中,显示了所建议实现的数值效率。

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