Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision
The positioning of lithium battery tabs in electric vehicles is a crucial aspect of the power battery assembly process. During the pre-tightening process of the lithium battery stack assembly, cells and foams undergo different deformations, leading to varying displacements of cells at different leve...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | World Electric Vehicle Journal |
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| Online Access: | https://www.mdpi.com/2032-6653/16/1/27 |
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| author | Yueda Xu Yanfeng Xing Hongbo Zhao Yufang Lin Lijia Ren Zhihan Zhou |
| author_facet | Yueda Xu Yanfeng Xing Hongbo Zhao Yufang Lin Lijia Ren Zhihan Zhou |
| author_sort | Yueda Xu |
| collection | DOAJ |
| description | The positioning of lithium battery tabs in electric vehicles is a crucial aspect of the power battery assembly process. During the pre-tightening process of the lithium battery stack assembly, cells and foams undergo different deformations, leading to varying displacements of cells at different levels. Consequently, determining tab positions poses numerous challenges during the pre-tightening process of the stack assembly. To address these challenges, this paper proposes a method for detecting feature points and calculating the displacement of lithium battery stack tabs based on the MicKey method. This research focuses on the cell tab, utilizing the hue, saturation, and value (HSV) color space for image segmentation to adaptively extract the cell tab region and further obtain the ROI of the cell tab. In order to enhance the accuracy of tab displacement calculation, a novel method for feature point detection and displacement calculation of lithium battery stacks based on the MicKey (Metric Keypoints) method is introduced. MicKey can predict the coordinates of corresponding keypoints in the 3D camera space through keypoint matching based on neural networks, and it can acquire feature point pairs of the subject to be measured through its unique depth reduction characteristics. Results demonstrate that the average displacement error and root mean square error of this method are 0.03 mm and 0.04 mm, respectively. Compared to other feature matching algorithms, this method can more consistently and accurately detect feature points and calculate displacements, meeting the positioning accuracy requirements for the stack pole ear in the actual assembly process. It provides a theoretical foundation for subsequent procedures. |
| format | Article |
| id | doaj-art-68c9ebc1f49f4b52997f327f3aa5a009 |
| institution | Kabale University |
| issn | 2032-6653 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | World Electric Vehicle Journal |
| spelling | doaj-art-68c9ebc1f49f4b52997f327f3aa5a0092025-01-24T13:52:48ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-01-011612710.3390/wevj16010027Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine VisionYueda Xu0Yanfeng Xing1Hongbo Zhao2Yufang Lin3Lijia Ren4Zhihan Zhou5School of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201600, ChinaSchool of Mechanical and Automotive Engineering, Shanghai University of Engineering Science, Shanghai 201600, ChinaPan Asia Technical Automotive Center Co., Ltd., Shanghai 201201, ChinaSAIC GM Power Technology (Shanghai) Co., Ltd., Shanghai 201206, ChinaSAIC GM Power Technology (Shanghai) Co., Ltd., Shanghai 201206, ChinaAvatr Technology (Chongqing) Co., Ltd., Chongqing 401120, ChinaThe positioning of lithium battery tabs in electric vehicles is a crucial aspect of the power battery assembly process. During the pre-tightening process of the lithium battery stack assembly, cells and foams undergo different deformations, leading to varying displacements of cells at different levels. Consequently, determining tab positions poses numerous challenges during the pre-tightening process of the stack assembly. To address these challenges, this paper proposes a method for detecting feature points and calculating the displacement of lithium battery stack tabs based on the MicKey method. This research focuses on the cell tab, utilizing the hue, saturation, and value (HSV) color space for image segmentation to adaptively extract the cell tab region and further obtain the ROI of the cell tab. In order to enhance the accuracy of tab displacement calculation, a novel method for feature point detection and displacement calculation of lithium battery stacks based on the MicKey (Metric Keypoints) method is introduced. MicKey can predict the coordinates of corresponding keypoints in the 3D camera space through keypoint matching based on neural networks, and it can acquire feature point pairs of the subject to be measured through its unique depth reduction characteristics. Results demonstrate that the average displacement error and root mean square error of this method are 0.03 mm and 0.04 mm, respectively. Compared to other feature matching algorithms, this method can more consistently and accurately detect feature points and calculate displacements, meeting the positioning accuracy requirements for the stack pole ear in the actual assembly process. It provides a theoretical foundation for subsequent procedures.https://www.mdpi.com/2032-6653/16/1/27lithium battery tabsmachine visiondisplacement measurementHSV |
| spellingShingle | Yueda Xu Yanfeng Xing Hongbo Zhao Yufang Lin Lijia Ren Zhihan Zhou Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision World Electric Vehicle Journal lithium battery tabs machine vision displacement measurement HSV |
| title | Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision |
| title_full | Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision |
| title_fullStr | Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision |
| title_full_unstemmed | Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision |
| title_short | Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision |
| title_sort | multi cell displacement measurement during the assembly of automotive power batteries based on machine vision |
| topic | lithium battery tabs machine vision displacement measurement HSV |
| url | https://www.mdpi.com/2032-6653/16/1/27 |
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