Development of multi-physics, multi-scale Li-ion FEM simulation framework
Lithium-ion (Li-ion) batteries play a vital in modern energy storage, powering a wide range of applications such as electronics, electric vehicles (EVs) and renewable energy systems. Due to their high energy density and efficiency they are being heavily adopted across consumer and industrial sectors.
Behaviour of Li-ion batteries become complex because of the coupled electrochemical, thermal, and mechanical processes that occur across multiple scales such as the electrolyte reactions at the microscale and the thermal processes and induced stresses at the macroscale.
A multiphysics, multiscale modeling approach is critical, as it integrates physical phenomena such as charge transport, ion diffusion, heat generation, and structural mechanics. Such a fully coupled modeling framework enables realistic simulations that reflect battery behavior under diverse realistic operating scenarios. In this work, we will develop a comprehensive large deformation multi-physics for the simulation of the Li-ion batteries. Our attempt will be to present the computational homogenization technique consistent with the Hill-Mandel condition.
The multi-scale simulation of the Li-ion batteries is a computationally intensive process, and thus our focus in the work will be to design the carse mesh accurate finite element methods. In that regard, we have observed that use of the conventional displacement based FEM algorithm give rise to the spurious stress in case of Li diffusion induced stress. To overcome this issue, we propose the use of the stress based hybrid finite element methods. In our early implementation, we have got the encouraging result with the small deformation case as shown below.
A 1-D beam is modeled with a prescribed concentration profile and the plot of diffusion induced stress is observed by using both the conventional and hybrid elements.
July 2023 - Dec 2023
Course
Advanced Fluid Mechanics
Wave Propagation
Grade
A-
B
CGPA 8.5
Jan2024 - Jun 2024
Course
Deep Learning For Physical Systems
Composite Materials
Grade
A
B-
CGPA 8.38
... will be updated
[1] Shailendra Rahi, Manish Agrawal, “Development of hybrid finite element algorithm for contact problems with friction”, the 26th
International Congress of Theoretical and Applied Mechanics (ICTAM 2024), Daegu, Republic of Korea, August 25-30, 2024.