This paper presents a risk assessment framework to evaluate the safety implications of internal resistance growth in EV batteries, focusing on NMC and LFP chemistries. How the resistance growth affects performance, efficiency, and thermal stability, posing safety risks during the battery lifecycle.
The framework integrates empirical and model-based estimation methods, including DCIR, EIS, historical regression, equivalent circuit models, and physics-based approaches. Simulations incorporate temperature, depth-of-discharge, and cycle count to predict resistance trends and their impact on power output and efficiency.
A scoring system that evaluates safety risks based on state-of-resistance, state-of-health, and risk indicators, aiding battery pack selection for second and third life applications. Results show that NMC and LFP cells exhibit distinct resistance growth patterns, emphasizing the need for chemistry-specific safety strategies.
The scoring system is a weightage based equation that values the state of resistance, state of health, estimation methods and safety levels to suggest the right cells for the right application in its second and third life.
This approach provides a structured method for evaluating battery safety and optimizing lifecycle management in EV applications