Trajectory analysis of ejected particles during thermal runaway of large-format lithium-ion cells

Thermal runaway (TR) in lithium-ion batteries is accompanied by rapid gas release and particle ejection, both of which present significant safety hazards. This work investigates the particle dynamics of TR-driven outgassing in a large-format prismatic nickel-manganese-cobalt oxide cell with a LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathode through controlled heater-induced initiation and high-speed optical diagnostics. A series of four experiments were conducted under free-jet and obstructed-jet configurations, with synchronized voltage, surface temperature, and visual data acquisition. A dedicated image-processing pipeline based on OpenCV and TrackPy processed high-speed recordings at 35,200 frames per second to extract projected two-dimensional particle trajectories, velocities, and ejection angles from a single free-jet test. The results indicate time-dependent particle discharge behavior characterized by high initial velocities, broad in-plane ejection angles, subsequent directional shifts and a varying projected cone width. The event specific particle velocities were found to be within the range reported in optical studies for small-format cells. Furthermore, ejection angle analysis revealed a broad outgassing process with a total in-plane width exceeding 180°. The findings demonstrate the event-resolved application of the proposed methodology for quantitative analysis of visible TR ejecta within the image plane and provide new insights into the transient nature of particle-driven venting.

Authors

Institutions

Publication Details

Journal
Journal of Energy Storage
Published
2026-10-30
DOI
https://doi.org/10.1016/j.est.2026.125218
Primary Topic
Advanced Battery Technologies Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Trajectory analysis of ejected particles during thermal runaway of large-format lithium-ion cells

Juergen Koehler, Stefan M. Goetz, Rezvan Alamian, Wilhelm J. Tegethoff et al.
6 links
Journal of Energy Storage
Advanced Battery Technologies Research
article

Trajectory analysis of ejected particles during thermal runaway of large-format lithium-ion cells

Juergen Koehler, Stefan M. Goetz, Rezvan Alamian, Wilhelm J. Tegethoff, Carsten Schilde, Frederik Andreas Novotny, Alexander Krause, Ashutosh Kale
article en

Abstract

Thermal runaway (TR) in lithium-ion batteries is accompanied by rapid gas release and particle ejection, both of which present significant safety hazards. This work investigates the particle dynamics of TR-driven outgassing in a large-format prismatic nickel-manganese-cobalt oxide cell with a LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) cathode through controlled heater-induced initiation and high-speed optical diagnostics. A series of four experiments were conducted under free-jet and obstructed-jet configurations, with synchronized voltage, surface temperature, and visual data acquisition. A dedicated image-processing pipeline based on OpenCV and TrackPy processed high-speed recordings at 35,200 frames per second to extract projected two-dimensional particle trajectories, velocities, and ejection angles from a single free-jet test. The results indicate time-dependent particle discharge behavior characterized by high initial velocities, broad in-plane ejection angles, subsequent directional shifts and a varying projected cone width. The event specific particle velocities were found to be within the range reported in optical studies for small-format cells. Furthermore, ejection angle analysis revealed a broad outgassing process with a total in-plane width exceeding 180°. The findings demonstrate the event-resolved application of the proposed methodology for quantitative analysis of visible TR ejecta within the image plane and provide new insights into the transient nature of particle-driven venting.

Journal of Energy StorageVol. 183
Audi (Germany) (DE), University of Kaiserslautern (DE), Technische Universität Braunschweig (DE)
Openalex Percentile: Top 23%
Advanced Battery Technologies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon