A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries
Lithium-ion power battery pack life, capacity and safety depend primarily on consistency between battery cells. However, inconsistencies between battery cells are inevitable due to the inherent variability in production processes and operational environments. In parallel circuits, battery management...
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MDPI AG
2025-02-01
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| Series: | World Electric Vehicle Journal |
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| author | Hanchi Hong Xiangxin Chen Luigi d’Apolito Yangqi Ye Shuiwen Shen |
| author_facet | Hanchi Hong Xiangxin Chen Luigi d’Apolito Yangqi Ye Shuiwen Shen |
| author_sort | Hanchi Hong |
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| description | Lithium-ion power battery pack life, capacity and safety depend primarily on consistency between battery cells. However, inconsistencies between battery cells are inevitable due to the inherent variability in production processes and operational environments. In parallel circuits, battery management systems can usually only monitor the total module current and terminal voltage, which results in limitations that lead to inter-unit inconsistency, reducing overall safety and energy efficiency. The conventional method of battery sorting involves analyzing static parameters such as capacity, internal resistance and voltage to ensure static consistency between cells. Nonetheless, cell-to-cell variations are more pronounced during dynamic and complex operations. The direct integration of static and dynamic features may result in data scale discrepancies and redundant information. Thus, the present study proposes a two-stage multi-parameter clustering method based on static and dynamic features. Initially, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was applied to sort abnormal batteries and identify the number of subsequent clusters, using discharge capacity, internal resistance and open-circuit voltage (OCV) as inputs. Then, a Principal Component Analysis (PCA) was used to downscale and extract features from the discharge voltage profile. The principal component data were used as inputs to the Self-Organizing Map (SOM) clustering algorithm, which uses its self-organized and unsupervised learning characteristics to mine more dynamic time-series features and complete the final clustering and sorting. Finally, the effectiveness of the two-stage sorting method in parallel circuits was verified by determining clustering evaluation indexes, as well as the cycle life and discharge curves of batteries reassembled in parallel. |
| format | Article |
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| issn | 2032-6653 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | MDPI AG |
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| series | World Electric Vehicle Journal |
| spelling | doaj-art-8a4217eed51543ae88afb738ed793ee82025-08-20T01:50:02ZengMDPI AGWorld Electric Vehicle Journal2032-66532025-02-0116312510.3390/wevj16030125A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion BatteriesHanchi Hong0Xiangxin Chen1Luigi d’Apolito2Yangqi Ye3Shuiwen Shen4School of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, ChinaSchool of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, ChinaSchool of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, ChinaSchool of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, ChinaSchool of Mechanical and Automotive Engineering, Xiamen University of Technology, Xiamen 361000, ChinaLithium-ion power battery pack life, capacity and safety depend primarily on consistency between battery cells. However, inconsistencies between battery cells are inevitable due to the inherent variability in production processes and operational environments. In parallel circuits, battery management systems can usually only monitor the total module current and terminal voltage, which results in limitations that lead to inter-unit inconsistency, reducing overall safety and energy efficiency. The conventional method of battery sorting involves analyzing static parameters such as capacity, internal resistance and voltage to ensure static consistency between cells. Nonetheless, cell-to-cell variations are more pronounced during dynamic and complex operations. The direct integration of static and dynamic features may result in data scale discrepancies and redundant information. Thus, the present study proposes a two-stage multi-parameter clustering method based on static and dynamic features. Initially, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) was applied to sort abnormal batteries and identify the number of subsequent clusters, using discharge capacity, internal resistance and open-circuit voltage (OCV) as inputs. Then, a Principal Component Analysis (PCA) was used to downscale and extract features from the discharge voltage profile. The principal component data were used as inputs to the Self-Organizing Map (SOM) clustering algorithm, which uses its self-organized and unsupervised learning characteristics to mine more dynamic time-series features and complete the final clustering and sorting. Finally, the effectiveness of the two-stage sorting method in parallel circuits was verified by determining clustering evaluation indexes, as well as the cycle life and discharge curves of batteries reassembled in parallel.https://www.mdpi.com/2032-6653/16/3/125lithium-ion batterytwo-stage sortingprincipal component analysisclustering algorithmparallel connection |
| spellingShingle | Hanchi Hong Xiangxin Chen Luigi d’Apolito Yangqi Ye Shuiwen Shen A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries World Electric Vehicle Journal lithium-ion battery two-stage sorting principal component analysis clustering algorithm parallel connection |
| title | A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries |
| title_full | A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries |
| title_fullStr | A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries |
| title_full_unstemmed | A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries |
| title_short | A Two-Stage Multi-Parameter-Based Sorting Method for Ensuring Consistency Between Parallel-Connected Lithium-Ion Batteries |
| title_sort | two stage multi parameter based sorting method for ensuring consistency between parallel connected lithium ion batteries |
| topic | lithium-ion battery two-stage sorting principal component analysis clustering algorithm parallel connection |
| url | https://www.mdpi.com/2032-6653/16/3/125 |
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