Live-stream infrared perception for lithium-ion battery thermal diagnosis.

ABSTRACT: Accurate thermal fault localization in densely packed lithium-ion battery packs is significantly challenged by mutual cell occlusion, hindering traditional single-perspective monitoring and thermal runaway prevention. To overcome this, we propose a novel two-stage thermal characterization and localization framework. Its core innovation uses real-time camera rotation to capture multi-perspective surface thermal images, effectively circumventing occlusion. Stage 1 uses a detection transformer (DETR) for coarse target characterization via video instance query and frame tracking. Stage 2 achieves precise cell-level fault localization using a 3D incoherent region detector combined with point quadtree-based mask fine-adjustment. Tested on Ansys Fluent-generated battery models under varying ambie

SUBMITTER: Tian L 

PROVIDER: S-EPMC12767187 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature