Study on Guided Wave Propagation Characteristics in Multilayered Porous Lithium Batteries Based on the Wave Finite Element Method
Accurately assessing the state of lithium-ion batteries (LiBs) is critical for both economic and safety considerations. Traditional methods for evaluating battery state are often expensive and imprecise. In contrast, ultrasonic technology can precisely evaluate the cycling state of batteries by capturing changes in mechanical properties during the cycling process, significantly enhancing reliability and safety. This study proposes a wave finite element method (WFEM) based on Floquet boundary conditions (BC) to investigate guided wave propagation characteristics in multilayer porous LiBs under different cycling states. The method uses the finite element software COMSOL Multiphysics to model a section of the waveguide and applies Floquet BC to establish an eigenvalue problem, simplifying its formulation. To improve computational efficiency, the porous material is reformulated based on Biot’s theory, replacing the displacement-based equations (u, u) with the displacement-pressure equations (u, p), which reduces computational resource consumption. To validate the feasibility and accuracy of the proposed method, the guided wave dispersion curves of LiBs under various cycling states were calculated and compared with results obtained using the global matrix method. Subsequently, experimental tests were conducted on LiBs using a scanning laser Doppler vibrometer (SLDV), and the frequency-wavenumber diagrams at different charge levels were extracted using the Matrix Pencil method, further confirming the effectiveness of the method.
Authors
- Yang Liu (ORCID: https://orcid.org/0000-0001-9517-3833)
- Zhoumo Zeng (ORCID: https://orcid.org/0000-0001-8220-598X)
- Shili Chen (ORCID: https://orcid.org/0000-0003-4718-169X)
- Jian Li (ORCID: https://orcid.org/0000-0002-0149-8299)
- Yaxun Gou
- Yitian Yan
Institutions
- Tianjin University (CN)
Publication Details
- Published
- 2024-09-22
- DOI
- https://doi.org/10.1109/uffc-js60046.2024.10793729
- Primary Topic
- Modular Robots and Swarm Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 0.00