Predictive Modeling and Sensitivity Analysis of Thermal Runaway in 800V Lithium-Ion Battery Pack Module Using DFSS Methodology

Thermal runaway in high-voltage lithium-ion battery modules should focus on critical safety and design challenges in electric vehicle applications, which need predictive methods that enhance passenger safety and support regulatory compliance. The primary purpose of a lithium-ion battery in an electric vehicle is to provide reliable energy storage while maintaining safe operation under different operating conditions. This study proposes a Design for Six Sigma (DFSS) methodology to virtually predict and correlate thermal runaway and its propagation in an 800V high-power lithium-ion battery module. Conventional propagation analysis relies heavily on physical testing, whereas the DFSS-based virtual framework enables cost-effective evaluation at early design stages. Input factors included are heat transfer pathways, which are sensitive to the temperature changes, as well as thermal propagation time. Control factors are the design or process parameters that engineers use to establish the functional performance of a system. The noise factors capture material variability and manufacturing tolerances affecting thermal properties. Output responses included the maximum cell temperature Versus time, thermal propagation time to adjacent cells, and total propagation duration across the module, measured in minutes. The validated 1D GT-SUITE model shows strong correlation with experimental data, confirming its reliability to predict thermal propagation time and supporting safer, thermally optimized battery pack designs. The validated model can be integrated into system (battery pack) level 1D thermal simulations, offering a calibrated model for future pack level propagation studies and supporting the development of safer, thermally optimized battery architectures.