An Microscopic Image-based Microstructure Modeling method for Predicting Battery Separators' Behavior
Publication Date: 2017-Apr-28
The IP.com Prior Art Database
A Microscopic Image-based Microstructure Modeling Method for Battery Separator
Lithium-ion battery technology is widely used in electric vehicles due to its high energy density. The mechanical behavior of the battery separator has a strong influence on the battery integrity when the battery is under external loads. In order to accurately predict the batteries’ responses to mechanical loads and other abusive conditions, it is critical to model the mechanical behavior and the microstructure morphology of the battery separator. However, all existing studies describe the anisotropic mechanical properties of battery separator using the phenomenological models. Such models have limited capability to accurately predict the nonlinear, anisotropic mechanical properties (e.g. elastic modulus, stress-strain curve) of the battery separator.
Furthermore, the phenomenological models cannot help the engineers to understand the underlying mechanism of battery thermal runaway either. The microstructure model is one of the key enablers for predicting the occurrence of the thermal event when battery deforms. It is important to capture the structural features on the micro/nano scale, such as the micro-porosity and micro-voids during the battery separator’s deformation. Therefore, a microscopic image-based microstructure modeling algorithm is needed for battery safety modeling.
Even though there are a great number of studies on microscopic imaging of the battery separators’ microstructure, none of them has accomplished a microstructure model based on the microscopic images. Due to the lack of battery separator microstructure modeling tools, there are several obstacles for electric vehicle safety design: (1) it is difficult, if not impossible, to understand the underlying physics that lead to battery thermal runaway in a deformation event; (2) there is no systematic way to guide the selection, design or manufacturing of the battery separator to satisfy the safety requirements. The current way, trial-and-error method, is time consuming and costly.
To address the aforementioned challenges, an industry first microscopic image-based microstructure modeling method is developed. The proposed method classifies image pixels into four different categories/phases: voids, thin polymer fibril (small thickness, high strength and high modulus), the thick polymer lamellae (large thickness, low strength and low modulus) and the high strain region in lamellae (large thickness, high strength and high modulus). They are assigned with different material properties in the Finite Element Analysis (FEA) model. The input is a Scanning Electron Microscopic (SEM) image of the battery separator. Low voltage SEM is preferred to avoid damaging the polymer microstructure. It is also recommended (not required) to coat the separator sample with gold for a good image contrast.
The proposed method consists of (1) a novel microstructure image processing module; (2) FEA of the microstru...