Autonomous Visual Detection of Defects from Battery Electrode Manufacturing-Reference-Cited by-同舟云学术

Autonomous Visual Detection of Defects from Battery Electrode Manufacturing

Published:2022-10-13 Issue:12 Volume:4 Page:2200142
ISSN:2640-4567
Container-title:Advanced Intelligent Systems
language:en
Short-container-title:Advanced Intelligent Systems

Author:

Choudhary Nirmal¹²,Clever Henning³,Ludwigs Robert³,Rath Michael⁴,Gannouni Aymen⁴,Schmetz Arno⁵,Hülsmann Tom⁵,Sawodny Julia⁶,Fischer Leon¹²,Kampker Achim³,Fleischer Juergen⁶,Stein Helge S.¹²^ORCID

Affiliation:

1. Helmholtz Institute Ulm (HIU) Helmholtzstr. 11 89081 Ulm Germany

2. Institute of Physical Chemistry (IPC) Karlsruhe Institute of Technology (KIT) Fritz-HaberWeg 2 76131 Karlsruhe Germany

3. Chair of Production Engineering of E-Mobility Components (PEM) RWTH Aachen University Bohr 12 52 072 Aachen Germany

4. Information Management in Mechanical Engineering (IMA) RWTH Aachen University Dennewartstr. 27 52068 Aachen Germany

5. Fraunhofer Research Institution for Battery Cell Production FFB Mendelstraße 11 48149 Münster Germany

6. WBK Institute of Production Science Karlsruhe Institute of Technology Kaiserstrasse 12 76131 Karlsruhe Germany

Funder

Bundesministerium für Bildung und Forschung

Deutsche Forschungsgemeinschaft

Horizon 2020

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202200142

Reference37 articles.

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2. Opportunities and Challenges of Lithium Ion Batteries in Automotive Applications

3. Beyond Expert‐Level Performance Prediction for Rechargeable Batteries by Unsupervised Machine Learning

4. Effect of electrode manufacturing defects on electrochemical performance of lithium-ion batteries: Cognizance of the battery failure sources

5. Coating and Drying Defects

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