All-solid-state batteries (ASSBs) have been considered as the next generation of lithium-ion batteries. Physics-based models have the advantage of providing internal electrochemical information. To promote physics-based models in real-time applications, in this study, a series of model reduction methods are applied to obtain a reduced-order model (ROM) for ASSBs. First, analytical solutions of the partial differential equations (PDEs) are derived by the Laplace transform. Then, the Padé approximation method is used to convert the transcendental transfer functions into lower order fractional transfer functions. Next, the concentration distributions in electrodes and electrolytes are approximated by parabolic and cubic functions, respectively. Due to the fast calculation of concentration distributions in real time, the equilibrium potential, overpotentials, and battery voltage can now be directly calculated. Compared with the original PDE-based model, the voltage errors of the proposed ROM are less than 2.6 mV. Compared with the voltage response of experimental data, a good agreement can be observed for the ROM under three large C-rates discharging conditions. The calculation time of ROM per step is within 0.2 ms, which means that it can be integrated into a battery management system. The proposed ROM achieves excellent performance and a better tradeoff between model fidelity and computational complexity.

中文翻译：

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全固态电池的降序电化学模型

全固态电池（ASSB）已被视为下一代锂离子电池。基于物理的模型具有提供内部电化学信息的优势。为了在实时应用中推广基于物理的模型，在这项研究中，应用了一系列模型缩减方法来获得ASSB的降阶模型（ROM）。首先，通过拉普拉斯变换得出偏微分方程（PDE）的解析解。然后，使用Padé逼近方法将先验传递函数转换为低阶分数传递函数。接下来，分别通过抛物线函数和三次函数来估计电极和电解质中的浓度分布。由于实时快速地计算浓度分布，因此平衡势能，超电势和电池电压现在可以直接计算出来。与原始的基于PDE的模型相比，所建议的ROM的电压误差小于2.6 mV。与实验数据的电压响应相比，在三种大的C速率放电条件下，ROM具有良好的一致性。ROM每步的计算时间在0.2毫秒内，这意味着它可以集成到电池管理系统中。所提出的ROM实现了出色的性能，并在模型保真度和计算复杂度之间取得了更好的折衷。在三个大的C速率放电条件下，可以观察到ROM的良好协议。ROM每步的计算时间在0.2毫秒内，这意味着它可以集成到电池管理系统中。所提出的ROM实现了出色的性能，并在模型保真度和计算复杂度之间取得了更好的折衷。在三个大的C速率放电条件下，可以观察到ROM的良好协议。ROM每步的计算时间在0.2毫秒内，这意味着它可以集成到电池管理系统中。所提出的ROM实现了出色的性能，并在模型保真度和计算复杂度之间取得了更好的折衷。