Multiphysics nature of Lithium-ion Battery safety issues

Doctoral Candidate Name: 
Yikai Jia
Mechanical Engineering

Safety issues of lithium-ion batteries (LIBs) are usually initiated from an internal short circuit (ISC) that can be triggered by external accidental abusive loadings. The generated heat and the increased temperature would lead to several complicated physio-chemical changes of the batteries, e.g., thermal runaway (TR). Thus, investigation of the multiphysics behaviors of lithium-ion batteries becomes a paramount task to understand the battery safety issues. Experimental characterization and numerical simulation are essential ways to understand the underlying nature of the multiphysics behavior of batteries. However, experimental observation may only provide insufficient data due to the limitation of experimental technology. Particularly, in-situ and operando experiment methodologies are limited. Multiphysics modeling is regarded as a critical and insightful tool to unravel the nonlinear and complicated behaviors. Machine learning (ML) model with data-driven methodology is another important tool to realize fast and accurate estimation and classification. Herein, an ML-based ISC risk evaluation model will be first developed based on the training dataset generated by the combination of experimental data and simulation data. A Representative Volume Element (RVE) based mechanical model, which can predict accurate mechanical behaviors at a much lower calculation time cost, will be established to assist the data generation. Next, an ML-based classifier will be developed to classify the cell’s safety levels under various work conditions. A multiphysics model will be developed to assist the generation of training data samples. Finally, two typical safety issues: defect and TR propagation are systematically studied. The safety risk of the defective batteries will be further evaluated. Electrochemical and mechanical characterization tests will be designed and conducted. The multiphysics model will be used to provide necessary auxiliary instructions of the related mechanisms. TR propagation behaviors of battery packs will be experimentally and numerically investigated. The battery pack TR model will be developed based on the single-cell multiphysics model.
This study comprehensively investigates the multiphysics behavior of LIB cells under mechanical abusive loadings, highlights the promise of combining the physical model with a data-driven model, and provides an innovative solution for the recognition of the battery safety risks for battery safety monitoring.

Defense Date and Time: 
Friday, April 1, 2022 - 1:30pm
Defense Location: 
Duke 324
Committee Chair's Name: 
Dr. Jun Xu
Committee Members: 
Dr. Jun Xu, Dr. Qiuming Wei, Dr. Robert Cox, Dr. Mesbah Uddin, Dr. Tao Hong