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Premature battery drain, swelling and fires/explosions in lithium-ion batteries have caused wide-scale customer concerns, product recalls, and huge financial losses in a wide range of products including smartphones, laptops, e-cigarettes, hoverboards, cars, and commercial aircraft.
Defect detection within LIBs requires advanced methodologies for three-dimensional defect localization, enabling the differentiation of electrodes, separators, and aluminum-plastic films within the battery layers.
Due to the inability to directly measure the internal state of batteries, there are technical challenges in battery state estimation, defect detection, and fault diagnosis. Ultrasonic technology, as a non-invasive diagnostic method, has been widely applied in the inspection of lithium-ion batteries in recent years.
Ultrasonic detection offers several distinct advantages over the aforementioned characterization methods for detecting gas defects in LIBs. Firstly, ultrasonic detection can penetrate the aluminum plastic film of batteries, allowing it to monitor tiny bubbles and defects deep inside the battery in real-time.
However, the use of batteries is associated with a number of significant risks, including the potential for thermal runaway and explosions. The meticulous inspection of LIBs is not only essential for guaranteeing their quality and functionality, but also for ensuring their safety.
Fault mechanisms LIBs suffer from potential safety issues in practice inherent to their energy-dense chemistry and flammable materials. From the perspective of electrical faults, fault modes can be divided into battery faults and sensor faults. 4.1. Battery faults
This capability is of critical importance for the identification of defects that could lead to battery failure or safety issues, and guide the optimization of LIBs with better safety …
Thirdly, it outlines the current status, main technological approaches, and challenges of ultrasonic technology in battery defect and fault diagnosis, including defect …
This paper addresses the safety risks posed by manufacturing defects in lithium-ion batteries, analyzes their classification and associated hazards, and reviews the research …
Premature battery drain, swelling and fires/explosions in lithium-ion batteries have caused wide-scale customer concerns, product recalls, and huge financial losses in a …
This research addresses the critical challenge of classifying surface defects in lithium electronic components, crucial for ensuring the reliability and safety of lithium batteries. With a scarcity of …
The calendering defects are easy to occur by applying incorrect parameters ... AI technology could be the key factor in developing the next generation of battery technology …
4 · Specifically, in lithium battery shell defect detection, it achieves an mAP50 of 97.0%, representing a 4.6% improvement over Yolov8n. Its parameters and FLOPs are reduced by …
In this paper, AIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect …
This capability is of critical importance for the identification of defects that could lead to battery failure or safety issues, and guide the optimization of LIBs with better safety …
This research addresses the critical challenge of classifying surface defects in lithium electronic components, crucial for ensuring the reliability and safety of lithium batteries.
In this paper, AIA DETR model is proposed by adding AIA (attention in attention) module into transformer encoder part, which makes the model pay more attention to correct defect …
Understanding the effect of electrode manufacturing defects on lithium-ion battery (LIB) performance is key to reducing the scrap rate and cost during cell manufacturing.
4 · Specifically, in lithium battery shell defect detection, it achieves an mAP50 of 97.0%, representing a 4.6% improvement over Yolov8n. Its parameters and FLOPs are reduced by …
3D Point Cloud-Based Lithium Battery Surface Defects Detection Using Region Growing Proposal Approach Zia Ur Rehman, Xin Wang, Abdulrahman Abdo Ali Alsumeri, Malak Abid Ali Khan, …
Compared with the traditional detection technology, the defect detection of lithium-ion battery using industrial CT detection technology has many advantages, including component measurement of ...
The battery system, as the core energy storage device of new energy vehicles, faces increasing safety issues and threats. An accurate and robust fault diagnosis technique is …
Understanding defect evolution and structural transformations constitutes a prominent research frontier for ultimately controlling the electrochemical properties of …
Premature battery drain, swelling and fires/explosions in lithium-ion batteries have caused wide-scale customer concerns, product recalls, and huge financial losses in a wide range of products ...
[1] Zhang M. F. 2020 Impact of new energy vehicles on automobile manufacturing technology and equipment Southern Agricultural Machinery 51 187 Google …
In the production process of lithium battery, the quality inspection requirements of lithium battery are very high. ... Research on detection algorithm of lithium battery surface …
Defect Detection in Lithium-Ion Battery Mengchao Yi1,2, Fachao Jiang1*, Languang Lu2*, ... Technology, Lanzhou, China Lithium-ion batteries are widely used in electric vehicles and …
Lithium-ion battery technology, first commercialized in 1991, has become popular for energy. ... Additional applications of CT scanning for lithium-ion battery defects …
In particular, we offer (1) a thorough elucidation of a general state–space representation for a faulty battery model, involving the detailed formulation of the battery system state vector and …
This research addresses the critical challenge of classifying surface defects in lithium electronic components, crucial for ensuring the reliability and safety of lithium batteries.