Uncertainty analysis of stack pressure in EV battery module systems using a phenomenological modeling approach

Abstract

Li-ion battery module systems, which are utilized to power electric vehicles (EVs), consist of a collection of battery cells that generate the necessary electrical energy and a structure designed to protect the battery system's interior components. However, a swelling effect, which results from internal composition changes that arise due to electrochemical reactions, causes the volume of the battery cells to change as the battery status changes (e.g., state of charge (SOC) and degradation). This volumetric change results in stack pressure evolution within the battery module, which leads to structural deformation and, eventually, failure of the module system. The objective of this research is to develop a method to reliably identify the stack pressure in the module level, considering the uncertainty in the system. A phenomenological model is employed to simply and statistically represent the complex mechanical behavior of the battery cells. An equivalent mechanical model is implemented to estimate the stack pressure within the module system. This paper presents three case studies that examine and compare the distributions of the stack pressure under different designs, utilizing the proposed method. The results of these case studies highlight the importance of uncertainty analysis in the design process to ensure robustness and reliability while maintaining fixed costs.