New energy battery end cover detection

Autoencoder-Enhanced Regularized Prototypical Network for New Energy

In order to ensure the safety and reliability of NEV batteries, fault detection technologies for NEV battery have been proposed and developed rapidly in last few years (Chen, Liu, Alippi, Huang, & Liu, 2022) particular, fault detection methods based on machine learning using information extracted from large amounts of new energy vehicle operational data have

SGNet:A Lightweight Defect Detection Model for New Energy

The quality of the current collector, an essential component in new energy vehicle batteries, is crucial for battery performance and significantly impacts the safety of vehicle occupants. However, detecting defects in battery current collector in real-time industrial applications with limited computational resources poses a major challenge. To address this, our paper proposes

Optimization Analysis of Power Battery Pack Box Structure for New

Optimization Analysis of Power Battery Pack Box Structure for New Energy Vehicles Congcheng Ma1(B), Jihong Hou1, Fengchong Lan2, and Jiqing Cheng2 1 Guangzhou Vocational College of Technology and Business, Guangzhou, Guangdong, China congchiey@163 2 School of Mechanical and Automotive Engineering, South China University of Technology, Guangzhou,

Safety management system of new energy vehicle power battery

The continuous progress of society has deepened people''s emphasis on the new energy economy, and the importance of safety management for New Energy Vehicle Power Batteries (NEVPB) is also increasing (He et al. 2021).Among them, fault diagnosis of power batteries is a key focus of battery safety management, and many scholars have conducted

DCS-YOLO: Defect detection model for new energy vehicle battery

The FPS reaches 147.1, and the detection accuracy of various defect categories is improved, especially Severely bad and No cover, and the detection recall rate

Towards Automatic Power Battery Detection: New Challenge

We conduct a comprehensive study on a new task named power battery detection (PBD), which aims to localize the dense cathode and anode plates endpoints from X-ray images to evaluate the quality of power batteries.

DGNet: An Adaptive Lightweight Defect Detection Model for New Energy

An end-to-end adaptive and lightweight defect detection model for the battery current collector (BCC), DGNet is proposed, which achieves higher detection accuracy and lower computational overhead, reaching the state-of-the-art (SOTA) level. As an essential component of the new energy vehicle battery, current collectors affect the performance of battery and are crucial to

Autoencoder-Enhanced Regularized Prototypical Network for New Energy

This network is proposed for new energy vehicle battery monitoring, which handles the serve class imbalance phenomenon in data samples. The data samples are processed by autoencoder with the addition of a regularized embedding strategy. Effective features of the data are extracted to construct more representative and mutually separated

New energy

This equipment is used to press and seal the cell cover, and pre-weld, seal welding, short-circuit test for cell cover and aluminum cases. The function includes battery scanning code module,

An intelligent detection approach for end-of-life power battery

The global new energy vehicle industry is currently experiencing significant growth, with China being the world''s leading producer and seller of new energy vehicles for seven consecutive years. 1 As of June 2023, China had sold 3,400,000 new energy vehicles, which is a 15% increase from the full year sales in 2021. These figures account for a global market share

An intelligent detection approach for end-of-life power battery

To address this issue, this research proposes a detection method for end-of-life power battery shell bolts. Based on market analysis, the target bolt for the retired power battery shell was identified. The bolt images were collected and preprocessed to create a custom dataset on the experimental platform. Four popular object detection

DCS-YOLO: Defect detection model for new energy vehicle battery

The FPS reaches 147.1, and the detection accuracy of various defect categories is improved, especially Severely bad and No cover, and the detection recall rate reaches 100%. This method has high target detection model efficiency and meets the requirements of real-time detection of battery collector defects.

Fault diagnosis of new energy vehicles based on improved

The new energy vehicle system is in the initial stage of application, so the probability of fault is greater. Therefore, its reliability urgently needs to be improved. In order to improve the fault diagnosis effect of new energy vehicles, this paper proposes a fault diagnosis system of new energy vehicle electric drive system based on improved machine learning and

Autoencoder-Enhanced Regularized Prototypical Network for New

This network is proposed for new energy vehicle battery monitoring, which handles the serve class imbalance phenomenon in data samples. The data samples are

An intelligent detection approach for end-of-life power

To address this issue, this research proposes a detection method for end-of-life power battery shell bolts. Based on market analysis, the target bolt for the retired power battery shell was identified. The bolt images

New energy

This equipment is used to press and seal the cell cover, and pre-weld, seal welding, short-circuit test for cell cover and aluminum cases. The function includes battery scanning code module, cleaning module, cell cover press module, cell cover and shell step detection module, cover pre-welding module, cover sealing module, short circuit test

Towards Automatic Power Battery Detection: New Challenge

We conduct a comprehensive study on a new task named power battery detection (PBD), which aims to localize the dense cathode and anode plates endpoints from X-ray images to evaluate

CN115752952A

The application relates to a new energy battery detection system and detection equipment, which belong to the technical field of battery detection, wherein through an arranged...

DGNet: An Adaptive Lightweight Defect Detection Model for New

In order to reduce application costs and conduct real-time detection with limited computing resources, we propose an end-to-end adaptive and lightweight defect detection

Safety management system of new energy vehicle power battery

Therefore, the fault diagnosis model based on WOA-LSTM algorithm proposed in the study can improve the safety of the power battery of new energy battery vehicles and

DGNet: An Adaptive Lightweight Defect Detection Model for New Energy

In order to reduce application costs and conduct real-time detection with limited computing resources, we propose an end-to-end adaptive and lightweight defect detection model for the battery current collector (BCC), DGNet.

An Electric Vehicle Battery and Management Techniques:

Fig. 1 shows the global sales of EVs, including battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs), as reported by the International Energy Agency (IEA) [9, 10].Sales of BEVs increased to 9.5 million in FY 2023 from 7.3 million in 2002, whereas the number of PHEVs sold in FY 2023 were 4.3 million compared with 2.9 million in 2022.

Global New Energy Battery X-Ray Intelligent Detection

Market Research Report Summary. Global New Energy Battery X-Ray Intelligent Detection Equipment Market 2023 by Manufacturers, Regions, Type and Application, Forecast to 2029 report is published on March 8, 2023 and has 95 pages in it. This market research report provides information about Manufacturers, Machinery, Industry & Manufacturing industry.

New energy

Suitable for lithium battery cover plate leak detection, dual station detection reasonable coordination of loading and unloading and leak detection process, greatly improve

New energy battery cover flatness detection

Using POMEAS 8055 spectral confocal sensor solution, non-contact measurement, compared with the traditional contact measurement method, it can avoid the occurrence of foreign objects and appearance wear on the product, and can accurately identify the flatness of the battery cover, and the measurement speed is fast, 10 seconds.

New energy

Suitable for lithium battery cover plate leak detection, dual station detection reasonable coordination of loading and unloading and leak detection process, greatly improve the detection beat; Helium, an inert gas, is selected as the tracer gas, which has the characteristics of high safety, low molecular weight, high penetration and strong

Safety management system of new energy vehicle power battery

Therefore, the fault diagnosis model based on WOA-LSTM algorithm proposed in the study can improve the safety of the power battery of new energy battery vehicles and reduce the probability of safety accidents during the driving process of new energy vehicles.

SOLARENERGY