论文标题

部分可观测时空混沌系统的无模型预测

Quantitative characterisation of the layered structure within lithium-ion batteries using ultrasonic resonance

论文作者

Huang, Ming, Kirkaldy, Niall, Zhao, Yan, Patel, Yatish, Cegla, Frederic, Lan, Bo

论文摘要

储层计算是预测湍流的有力工具,其简单的架构具有处理大型系统的计算效率。然而,其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间,然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用,该系统模拟了湍流的若干特征。我们表明,使用径向基函数作为非线性投影器,即使只有部分观测并且不知道控制方程,也能稳健地捕捉复杂的系统非线性。最后,我们表明,当测量稀疏、不完整且带有噪声,甚至控制方程变得不准确时,我们的网络仍然可以产生相当准确的预测,从而为实际湍流系统的无模型预测铺平了道路。

Lithium-ion batteries (LIBs) are becoming an important energy storage solution to achieve carbon neutrality, but it remains challenging to characterise their internal states for the assurance of performance, durability and safety. This work reports a simple but powerful non-destructive characterisation technique, based on the formation of ultrasonic resonance from the repetitive layers within LIBs. A physical model is developed from the ground up, to interpret the results from standard experimental ultrasonic measurement setups. As output, the method delivers a range of critical pieces of information about the inner structure of LIBs, such as the number of layers, the average thicknesses of electrodes, the image of internal layers, and the states of charge variations across individual layers. This enables the quantitative tracking of internal cell properties, potentially providing new means of quality control during production processes, and tracking the states of health and charge during operation.

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