Representative Volume Element Analysis of Fluid-Structure Interaction Effect on Graphite Powder Based Active Material for Lithium-Ion Batteries

2017 ◽  
Vol 24 (1) ◽  
pp. 17-23
Author(s):  
Jin Chul Yun ◽  
Seong Jin Park
2021 ◽  
pp. 073168442094118
Author(s):  
Qi Wu ◽  
Hongzhou Zhai ◽  
Nobuhiro Yoshikawa ◽  
Tomotaka Ogasawara ◽  
Naoki Morita

A novel localization approach that seamlessly bridges the macro- and micro-scale models is proposed and used to model the forming-induced residual stresses within a representative volume element of a fiber reinforced composite. The approach uses a prescribed boundary that is theoretically deduced by integrating the asymptotic expansion of a composite and the equal strain transfer, thus rendering the simulation setting to be easier than conventional approaches. When the localization approach is used for the finite element analysis, the temperature and residual stresses within an ideal cubic representative volume element are precisely simulated, given a sandwiched thermoplastic composite is formed under one-side cooling condition. The simulation results, after being validated, show that the temperature gradient has an impact on the local residual stresses, especially on the in-plane normal stress transverse to the fiber, and consequently, influences the structural deformation. This newly designed localization approach demonstrates the advantages of enhanced precision and reduced computational cost owing to the fast modeling of the finely meshed representative volume element. This is beneficial for a detailed understanding of the actual residual stresses at the micro-scale.


Author(s):  
Seyed Hamid Reza Sanei ◽  
Randall Doles

Abstract The aim of this study is to present a representative volume element (RVE) for nanocomposites with different microstructural features using a stochastic finite element approach. To that end, computer-simulated microstructures of nanocomposites were generated to include a variety of uncertainty present in geometry, orientation, and distribution of carbon nanotubes. Microstructures were converted into finite element models based on an image-based approach for the determination of elastic properties. For each microstructure type, 50 realizations of synthetic microstructures were generated to capture the variability as well as the average values. Computer-simulated microstructures were generated at different length scales to determine the change in mechanical properties as a function of length scale. A representative volume element is defined at a length scale beyond which no change in variability is observed. The results show that there is no universal RVE applicable to all properties and microstructures; however, the RVE size is highly dependent on microstructural features. Microstructures with agglomeration tend to require larger RVE. Similarly, random microstructures require larger RVE when compared with aligned microstructures.


2017 ◽  
Vol 47 (3) ◽  
pp. 281-293 ◽  
Author(s):  
Ali Ghorbani Kashkooli ◽  
Amir Amirfazli ◽  
Siamak Farhad ◽  
Dong Un Lee ◽  
Sergio Felicelli ◽  
...  

Author(s):  
Jin Chul Yun ◽  
Seong Jin Park

In this study, a representative volume element (RVE) homogenization approach is proposed to predict the mechanical properties of a lithium-ion battery (LIB) cell, module, and pack in an electric vehicle (EV). Different RVE models for the LIB jellyroll and module are suggested. Various elastic properties obtained from RVE analyses were compared to the analytic solution. To validate the approach suggested, the elastic responses of two types of homogenized LIB module for various loading cases were compared to the model where all the jellyroll and module components were described fully. Additionally, parametric studies were conducted to determine the relationship between design parameters of the jellyroll components and the elastic behavior of LIB jellyroll and module. The results obtained in this study provide useful information for both LIB cell developers, at the concept design stage, and engineers of electric vehicles who want to predict the mechanical safety of a battery pack.


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