Sensor Fault Detection of Lithium-Ion Batteries Based on Extended Kalman Filter

Masri, Bushra; Al-Sheikh, Hiba; Moubayed, Nazih

doi:10.1109/icecce49384.2020.9179416

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2023

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“…Utilising a residual modelbased analysis method, this paper concentrates on sensor troubleshooting in lithium-ion batteries. For defect detection, it utilises a modified Kalman filter and a generalised likelihood ratio test, as demonstrated by simulations [4]. Internal (ISC) and external (ESC) battery short circuit detection is crucial for avoiding thermal damage in Lithium-Ion Batteries (LIBs).…”

Section: Introductionmentioning

confidence: 99%

A Thermal Image based Fault Detection in Electric Vehicle Battery Cells Utilizing CNN U-Net Model

Senthilraj

2023

IJRITCC

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It entails the formation of thermal images from battery cells under different conditions, capturing crucial thermal patterns such as hotspots, insulation degradation, and overheating. For robust model training, data preprocessing and augmentation techniques are applied. The U-Net model, known for its expertise in semantic segmentation tasks, is applied to evaluate thermal images and to detect fault-related features. The results demonstrate the U-Net's unique precision, sensitivity, and specificity in detecting thermal anomalies. This research adds to the improvement of the safety and dependability of EV battery systems, with applications in the electric mobility and automotive industries.

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Section: Introductionmentioning

confidence: 99%