Lithium-ion batteries (LIBs) are instrumental for electric vehicles, but safety is a concern due to thermal runaway (TR) events. In this study, an in situ observation method for TR and its propagation (TRP) in LIB electrodes is presented, employing high-frequency induction heating as the TR triggering method. The non-contact, rapid heating.
How to detect internal defects in lithium-ion batteries?
Detection of internal defects in lithium-ion batteries using lock-in thermography Blister defect detection based on convolutional neural network for polymer lithium-ion battery Process-product interdependencies in lamination of electrodes and separators for lithium-ion batteries
Do lithium-ion cells have foreign matter defects?
When the lithium-ion cell has an internal short circuit, the risk of thermal runaway might increase, and even battery spontaneous combustion would be triggered, endangering people's lives. Therefore, the research on foreign matter defects of lithium-ion cells is currently a hotspot.
Does the detection rate of foreign matter defects improve battery quality?
Experiment results show that the proposed method's detection rate is improved significantly. The increase in the detection rate of foreign matter defects is beneficial to improving battery quality and safety. 1. Introduction
How can a battery management system improve the safety of foreign matter defect cells?
Undoubtedly, online monitoring of the operational status of the cell through the battery management system (BMS), to some degree, could reduce incidences of safety accidents induced by the foreign matter defect cell. However, it is more important to conduct quality control and improve the detection rate of defect cells during manufacturing.
Is there a short circuit detection method for lithium ion batteries?
A Novel Al–Cu Internal Short Circuit Detection Method for Lithium-Ion Batteries Based on on-Board Signal Processing. J. Energy Storage 2022, 52, 104748. [ Google Scholar] [ CrossRef]
How to prevent false detection of lithium-ion cells?
It is generally believed that the cell with a high K -value should be abnormal, while the cell with a low K -value should be normal. Therefore, to prevent false detection, the imported OCV- K dataset of lithium-ion cells needs to be preprocessed. Firstly, sort all samples in the OCV- K dataset in descending order of K -value.