In this article, we develop a 3D, continuum-level damage model implemented on statistically generated Li${}_x$Ni_0.5Mn_0.3Co_0.2O${}_2$ (NMC 532) secondary cathode particles. The primary motivation of the particle-level model is to inform cathode-particle design through detailed exploration of the influence of secondary and primary particle sizes on the damage predicted during operation, and determine charging profiles that reduce cathode fracture. The model considers NMC 532 secondary particles containing an agglomeration of anisotropic, randomly oriented grains. These brittle, Ni-based cathodes are prone to mechanical degradation, which reduces overall battery cycle life. The model predicts that secondary-particle fracture is primarily due to non-ideal grain interactions and high-rate charge demands. The model predicts that small secondary-particles with large grains develop significantly less damage than larger secondary particles with small grains. The model predicts most of the chemo-mechanical damage accumulates in the first few cycles. The chemo-mechanical model predicts monotonically increasing capacity fade with cycling and rate. Comparing to experimental results, the model is well suited for capturing initial capacity fade mechanisms, but additional physics is required to capture long-term capacity fade effects.

在本文中，我们开发了一个在统计生成的 Li 上实现的 3D 连续介质级损伤模型${}_X$Ni _0.5 Mn _0.3 Co _0.2 O${}_2$(NMC 532) 二次阴极颗粒。粒子级模型的主要动机是通过详细探索二次和一次粒子尺寸对操作期间预测的损坏的影响来为阴极粒子设计提供信息，并确定减少阴极断裂的充电曲线。该模型考虑了 NMC 532 二次粒子，其中包含各向异性、随机取向的晶粒团聚体。这些易碎的镍基阴极容易发生机械退化，从而降低整体电池循环寿命。该模型预测二次粒子断裂主要是由于非理想的晶粒相互作用和高速率充电需求。该模型预测，与具有小晶粒的较大二次粒子相比，具有大晶粒的小二次粒子产生的损伤要小得多。该模型预测大部分化学机械损伤会在前几个循环中累积。化学机械模型预测随着循环和速率单调增加的容量衰减。与实验结果相比，该模型非常适合捕获初始容量衰减机制，但需要额外的物理来捕获长期容量衰减效应。