材料科学
表征(材料科学)
阳极
原位
涂层
反向
压缩(物理)
复合材料
电极
纳米技术
化学
几何学
数学
物理化学
有机化学
作者
Tian Xiao,Pengfei Ying,Yong Xia
摘要
<div class="section abstract"><div class="htmlview paragraph">In this decade, the detailed multi-layer FE model is always applied for investigating the mechanical behavior of Li-ion batteries under mechanical abuse. However, establishing a detailed model of different types of batteries requires a series of material characterization of components. To improve the efficiency of the procedure of component calibration, we introduce a procedure of automatic coating material characterization as an example to represent the strategy. The proposed method is constructing a response solver through MATLAB to predict the mechanical behavior of the coating specimen's representative volume element (RVE) under designated test conditions. The coating material is represented through Drucker-Prager-Cap (DPC) model. All parameters, including boundary conditions and material parameters, are included in this solver. With the help of this solver, the optimized material parameters can be quickly obtained after minimizing the error function of test results and predicted response through the Genetic Algorithm (GA). For validation, the optimum parameters obtained from this process are input into the complete model in ABAQUS. As a result, the mechanical response of the FE model shows consistency with test results, which proves the feasibility and high efficiency of this automatic approach. Moreover, this method offers the great potential of this automated strategy for similar engineering applications.</div></div>
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