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A 0D/1D Methodology for Estimating Critical Parameters in Thermal Runaway Tests of Lithium-Ion Batteries in Closed Volumes Universitat Politecnica de Valencia

SAE Technical Papers (1906-current) Available online

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Format:
Book
Conference/Event
Author/Creator:
Garcia, Antonio, author.
Contributor:
Gómez-Soriano, Alejandro
Marco-Gimeno, Javier
Micó, Carlos
Conference Name:
17th International Conference on Engines and Vehicles (2025-09-14 : Capri, Italy)
Language:
English
Physical Description:
1 online resource cm
Place of Publication:
Warrendale, PA SAE International 2025
Summary:
The ongoing shift toward electrification, particularly in the transport and energy sectors, has intensified the deployment of lithium-ion batteries (LIBs). While LIBs offer high energy density and efficiency, their increasing use also brings significant safety challengesmost critically, the risk of thermal runaway (TR) in confined environments. This study presents a fast and structured zero-dimensional/one-dimensional (0D/1D) methodology for estimating key parameters associated with TR events in sealed volumes. The model integrates empirical correlations, energy-based mass estimation approaches, and simplified combustion simulations to assess pressure and temperature rise during TR. Experimental vented mass and gas composition dataobtained through sealed canister testingserve as the basis for the simulation inputs. A numerical procedure combining mixing dynamics and adiabatic combustion is used to predict critical outcomes such as maximum overpressure and peak temperature. Validation against in-house TR experiments with cylindrical NMC cells in 22-liter canisters demonstrates the method's ability to capture the pressure evolution trend with increasing capacity. Results further highlight format- and chemistry-dependent behaviors, such as oxygen-limited combustion regimes and their impact on thermal and pressure profiles. This generalizable and computationally efficient framework supports early-stage safety assessments and pre-dimensioning of battery energy storage systems (BESS), contributing to safer and more predictable TR analysis in LIBs
Notes:
Vendor supplied data
Publisher Number:
2025-24-0150
Access Restriction:
Restricted for use by site license

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