A MODEL-BASED RISK AND RELIABILITY ASSESSMENT OF A SECOND-LIFE EV BATTERY ENERGY STORAGE SYSTEM

Abstract

Lithium-ion batteries are widely used in energy storage applications because they are flexible, efficient, and scalable. However, as the electric vehicle market continues to grow, many batteries reach the end of their vehicle service life, raising concerns about significant waste generation. Some procedures allow these batteries to be repurposed for second-life applications. One viable approach is reusing these batteries in energy storage systems to provide a more sustainable solution. However, ensuring that these second-life systems operate safely is essential to prevent risks to people and the environment. To ensure operational integrity, diverse risk assessment frameworks can be employed to identify vulnerabilities and evaluate system reliability. Therefore, identifying the components that are most vulnerable to failure is essential for mitigating risks in these systems. This work presents a multi-stage analytical framework that unifies risk and reliability analyses within a model-based systems engineering (MBSE) architecture to identify and assess potentialsystem risks. This project presents the procedure used to apply these methodologies and describes how the process evolved from manual qualitative assessments to an automated, model-based approach. Using this framework, the analysis suggests that the most significant risks reside in the auxiliary systems that maintain optimal operating conditions. Therefore, prioritizing the reliability and monitoring of these components is essential for the safe and sustainable deployment of second-life battery energy storage systems.