PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
March 29, 20260 citations

Utilization of DEM Simulations to Quantify Cell Level Thickness and Volume Changes in Large Format Pouch Cells

View Full Paper
HTHunter TeelTGTaylor R. GarrickBKBrian J. Koch

Key Points

  • This research aims to model and quantify the effects of volume changes in lithium ion battery cells on electrode performance.
  • Created a 3D representation of a lithium ion battery cell using discrete element method (DEM)
  • Modeled porous electrode volume changes during operation
  • Utilized a representative volume element approach and multi-species reaction model to analyze effects on cell operation
  • Identified significant effects of electrode volume changes on strain and porosity during operation
  • Predictions indicate challenges in experimentally capturing porosity changes
  • Insights gained are crucial for developing high energy density battery cells to manage volume changes effectively

Abstract

In this work, a 3D representation of a lithium ion electric vehicle battery cell was created and modeled through the discrete element method (DEM) to capture the porous electrode volume change during cell operation and its effects on electrode strain, porosity changes, and pressure generation for each electrode. This was coupled with a representative volume element approach and the multi species reaction model to quantify the impact of these changes at an electrode level have on the cell level operation. Results on both the electrode level and cell level response were discussed to give insights on how the volume changes contribute to both strain and porosity changes and the potential effects these changes have on the electrochemical response of the generated representative cells. Predictions on the cell level response, particularly for porosity changes which can be difficult to capture experimentally, are essential for the further development of high energy density cells that utilize unique chemistries prone to high levels of volume change such as silicon and silicon oxides. The ability to predict the active material volume change and its nuances will be informative and essential to rapidly develop and design cells for both automotive and grid storage applications.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Teel et al. (2024) studied this question.

synapsesocial.com/papers/69c8c28cde0f0f753b39ce47https://doi.org/10.1149/1945-7111/ad749e">https://doi.org/10.1149/1945-7111/ad749e</a></p
Ask AI
Helpful
Bookmark
Share
View Full Paper