电池(电)
编码(内存)
计算机科学
材料科学
热力学
物理
功率(物理)
人工智能
作者
Zhe-Tao Sun,Shiwei Chen,Teng Zhao,Yunlong Guo,Zhenli Xu,Shenggao Zhou,Shou‐Hang Bo
摘要
The propagation of physicochemical heterogeneity from particles to electrodes under galvanostatic cycling conditions largely determines battery performance but is often computationally unreachable. We formulate a Real 2D (R2D) full-battery model via an electrode-adaptive mathematical framework that addresses the electrochemically correlated nonlinear current-potential responses of the electrodes. This allows us to quantify the impact of multiphysics coupling on cycling performance in emerging solid-state batteries. R2D advances the modeling efficiency and can be generally applied to heterogeneous battery systems, providing a new pathway for accurate full battery simulations.
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