{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T20:40:01Z","timestamp":1773780001472,"version":"3.50.1"},"reference-count":38,"publisher":"Public Library of Science (PLoS)","issue":"3","license":[{"start":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T00:00:00Z","timestamp":1773705600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>With the development of science and technology, lithium batteries, as important energy storage devices, have become a research hotspot for fault diagnosis. In response to the shortcomings of traditional fault diagnosis techniques in processing complex signals and extracting key features, a high-performance lithium battery fault diagnosis model is constructed by combining the high-dimensional representation ability of a two-dimensional convolutional neural network (2DCNN) with the decomposition stability of an optimized empirical mode decomposition (EMD) method. The study first uses an improved EMD algorithm to process the voltage data of lithium batteries and extract fault features. Moreover, the processed data are input into 2DCNN model for training and classification. The experiment results showed that the fault feature information consistency of the research designed model was 98.7% when the iteration number reached 600. The feature recognition accuracy dropped to 99.2% when the image contained 70 features. The running time in all 7 data groups was significantly lower than other methods, with the highest being below 6ms. The results indicate that the designed lithium battery fault diagnosis model has improved the accuracy and efficiency of fault diagnosis. This can provide new technological means for lithium battery fault diagnosis and helping to promote the further development and application of lithium battery technology.<\/jats:p>","DOI":"10.1371\/journal.pone.0344847","type":"journal-article","created":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T17:24:46Z","timestamp":1773768286000},"page":"e0344847","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Lithium battery fault diagnosis by integrating improved EMD decomposition algorithm and 2DCNN"],"prefix":"10.1371","volume":"21","author":[{"given":"Xiaofei","family":"Yin","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangfei","family":"Meng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haofei","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Like","family":"Zhong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Zhan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6655-6317","authenticated-orcid":true,"given":"Yang","family":"Pu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2026,3,17]]},"reference":[{"issue":"1","key":"pone.0344847.ref001","first-page":"30","article-title":"Designing electrolytes and interphases for high-energy lithium batteries","author":"H Wan","year":"2024","journal-title":"Nat Rev Chem"},{"issue":"2","key":"pone.0344847.ref002","doi-asserted-by":"crossref","first-page":"4583","DOI":"10.1109\/TTE.2023.3305999","article-title":"Hierarchical power management system for a fuel cell\/battery hybrid electric scooter","volume":"10","author":"S-Y Chen","year":"2024","journal-title":"IEEE Trans Transp Electrific"},{"issue":"11","key":"pone.0344847.ref003","doi-asserted-by":"crossref","first-page":"10967","DOI":"10.1109\/TII.2023.3242580","article-title":"Integrated Optimal energy management and sizing of hybrid battery\/flywheel energy storage for electric vehicles","volume":"19","author":"A Mehraban","year":"2023","journal-title":"IEEE Trans Ind Inf"},{"issue":"1","key":"pone.0344847.ref004","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1007\/s42835-023-01533-9","article-title":"A lithium-ion batteries fault diagnosis method for accurate coulomb counting state-of-Charge Estimation","volume":"19","author":"C-S Huang","year":"2023","journal-title":"J Electr Eng Technol"},{"issue":"4","key":"pone.0344847.ref005","doi-asserted-by":"crossref","first-page":"574","DOI":"10.1049\/itr2.12217","article-title":"Battery voltage fault diagnosis for electric vehicles considering driving condition variation","volume":"18","author":"H Zhang","year":"2022","journal-title":"IET Intelligent Trans Sys"},{"issue":"7","key":"pone.0344847.ref006","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1080\/15435075.2023.2260019","article-title":"Fault diagnosis of lithium-ion batteries based on voltage dip behavior","volume":"21","author":"C Chang","year":"2023","journal-title":"International Journal of Green Energy"},{"issue":"15","key":"pone.0344847.ref007","doi-asserted-by":"crossref","first-page":"16481","DOI":"10.1109\/JSEN.2023.3285531","article-title":"Artificial intelligence technique-based EV powertrain condition monitoring and fault diagnosis: a review","volume":"23","author":"X Zhang","year":"2023","journal-title":"IEEE Sensors J"},{"issue":"3","key":"pone.0344847.ref008","doi-asserted-by":"crossref","first-page":"1831","DOI":"10.1007\/s00202-021-01426-y","article-title":"Fault diagnosis for electric vehicle lithium batteries using a multi-classification support vector machine","volume":"104","author":"F Deng","year":"2021","journal-title":"Electr Eng"},{"issue":"12","key":"pone.0344847.ref009","doi-asserted-by":"crossref","first-page":"2828","DOI":"10.1080\/15435075.2024.2332331","article-title":"Fault diagnosis of lithium-ion batteries based on wavelet packet decomposition and Manhattan average distance","volume":"21","author":"L Liao","year":"2024","journal-title":"International Journal of Green Energy"},{"issue":"10","key":"pone.0344847.ref010","first-page":"1916","article-title":"A diagnosis method based on depthwise separable convolutional neural network for the attachment on the blade of marine current turbine","volume":"235","author":"B Xin","year":"2020","journal-title":"Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering"},{"issue":"2","key":"pone.0344847.ref011","doi-asserted-by":"crossref","first-page":"1897","DOI":"10.1007\/s42417-023-00949-x","article-title":"Fault diagnosis of rolling bearings based on the improved symmetrized dot pattern enhanced convolutional neural networks","volume":"12","author":"X Liu","year":"2023","journal-title":"J Vib Eng Technol"},{"issue":"1","key":"pone.0344847.ref012","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1109\/TEC.2023.3306804","article-title":"CEEMD-fuzzy control energy management of hybrid energy storage systems in electric vehicles","volume":"39","author":"Y Shen","year":"2023","journal-title":"IEEE Transactions on Energy Conversion"},{"issue":"7","key":"pone.0344847.ref013","doi-asserted-by":"crossref","first-page":"9865","DOI":"10.1109\/TVT.2024.3376711","article-title":"An integrated self-modularized battery equalizer and supercapacitor charger for hybrid electric vehicle energy storage system","volume":"73","author":"X Tan","year":"2024","journal-title":"IEEE Trans Veh Technol"},{"issue":"1","key":"pone.0344847.ref014","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1109\/JSEN.2022.3223980","article-title":"A fast and adaptive empirical mode decomposition method and its application in rolling bearing fault diagnosis","volume":"23","author":"Y Li","year":"2023","journal-title":"IEEE Sensors J"},{"issue":"8","key":"pone.0344847.ref015","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1007\/s11265-023-01845-z","article-title":"Application of EMD combined with deep learning and knowledge graph in bearing fault","volume":"95","author":"B Qi","year":"2023","journal-title":"J Sign Process Syst"},{"issue":"12","key":"pone.0344847.ref016","doi-asserted-by":"crossref","first-page":"11999","DOI":"10.1007\/s13369-021-05807-0","article-title":"Detection of local gear tooth defects on a multistage gearbox operating under fluctuating speeds using DWT and EMD analysis","volume":"46","author":"V Inturi","year":"2021","journal-title":"Arab J Sci Eng"},{"issue":"1","key":"pone.0344847.ref017","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1007\/s10043-023-00855-3","article-title":"Consideration of image processing system for high visibility of display using aerial imaging optics","volume":"31","author":"H Kikuta","year":"2023","journal-title":"Opt Rev"},{"issue":"2","key":"pone.0344847.ref018","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1007\/s11708-023-0891-7","article-title":"Machine learning and neural network supported state of health simulation and forecasting model for lithium-ion battery","volume":"18","author":"N Qi","year":"2023","journal-title":"Front Energy"},{"issue":"11","key":"pone.0344847.ref019","doi-asserted-by":"crossref","first-page":"1284","DOI":"10.1038\/s41560-023-01355-z","article-title":"Energy consumption of current and future production of lithium-ion and post lithium-ion battery cells","volume":"8","author":"F Degen","year":"2023","journal-title":"Nat Energy"},{"issue":"11","key":"pone.0344847.ref020","doi-asserted-by":"crossref","first-page":"11541","DOI":"10.1109\/TIE.2021.3125563","article-title":"Comprehensive analysis of linear and nonlinear equivalent circuit model for GaAs-PIN Diode","volume":"69","author":"A Zhang","year":"2022","journal-title":"IEEE Trans Ind Electron"},{"issue":"3","key":"pone.0344847.ref021","doi-asserted-by":"crossref","first-page":"3","DOI":"10.23919\/CJEE.2023.000007","article-title":"Experimental study on the effect of state of charge on failure propagation characteristics within battery modules","volume":"9","author":"K Li","year":"2023","journal-title":"Chin J Electr Eng"},{"issue":"3","key":"pone.0344847.ref022","doi-asserted-by":"crossref","first-page":"4726","DOI":"10.1109\/TTE.2023.3247614","article-title":"Remaining useful life prediction for lithium-ion batteries with a hybrid model based on TCN-GRU-DNN and dual attention mechanism","volume":"9","author":"L Li","year":"2023","journal-title":"IEEE Trans Transp Electrific"},{"issue":"3","key":"pone.0344847.ref023","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1002\/cnl2.31","article-title":"Progress and prospect on the recycling of spent lithium\u2010ion batteries: Ending is beginning","volume":"1","author":"J Yang","year":"2022","journal-title":"Carbon Neutralization"},{"issue":"8","key":"pone.0344847.ref024","doi-asserted-by":"crossref","first-page":"12142","DOI":"10.1109\/JSEN.2024.3370739","article-title":"Aging and echelon utilization status monitoring of power batteries based on improved EMD and PCA of acoustic emission","volume":"24","author":"K Zhang","year":"2024","journal-title":"IEEE Sensors J"},{"issue":"40","key":"pone.0344847.ref025","doi-asserted-by":"crossref","first-page":"56580","DOI":"10.1007\/s11356-021-14591-1","article-title":"Short-term prediction of carbon emissions based on the EEMD-PSOBP model","volume":"28","author":"W Sun","year":"2021","journal-title":"Environ Sci Pollut Res Int"},{"issue":"8","key":"pone.0344847.ref026","doi-asserted-by":"crossref","first-page":"6439","DOI":"10.1007\/s11071-024-09389-y","article-title":"An intelligent bearing fault diagnosis framework: one-dimensional improved self-attention-enhanced CNN and empirical wavelet transform","volume":"112","author":"Z Dong","year":"2024","journal-title":"Nonlinear Dyn"},{"issue":"1","key":"pone.0344847.ref027","doi-asserted-by":"crossref","first-page":"43","DOI":"10.47852\/bonviewAIA2202524","article-title":"Distribution alignment using complement entropy objective and adaptive consensus-based label refinement for partial domain adaptation","volume":"1","author":"S Choudhuri","year":"2022","journal-title":"Artificial Intelligence Applications"},{"issue":"4","key":"pone.0344847.ref028","doi-asserted-by":"crossref","first-page":"2475","DOI":"10.1177\/14759217231202543","article-title":"A rolling bearing fault diagnosis method based on a convolutional neural network with frequency attention mechanism","volume":"23","author":"H Zhou","year":"2023","journal-title":"Structural Health Monitoring"},{"issue":"3","key":"pone.0344847.ref029","first-page":"145","article-title":"Adapting a swin transformer for license plate number and text detection in drone images","volume":"1","author":"S Pal","year":"2023","journal-title":"Artif Intell Appl"},{"issue":"12","key":"pone.0344847.ref030","doi-asserted-by":"crossref","first-page":"11776","DOI":"10.1109\/TII.2023.3252407","article-title":"Interpretable incremental voltage\u2013current representation attention convolution neural network for nonintrusive load monitoring","volume":"19","author":"L Yin","year":"2023","journal-title":"IEEE Trans Ind Inf"},{"issue":"12","key":"pone.0344847.ref031","article-title":"An adaptive snow ablation-inspired particle swarm optimization with its application in geometric optimization","volume":"57","author":"G Hu","year":"2024","journal-title":"Artif Intell Rev"},{"issue":"18","key":"pone.0344847.ref032","doi-asserted-by":"crossref","first-page":"27391","DOI":"10.1007\/s11042-023-14478-y","article-title":"Cattle identification system: a comparative analysis of SIFT, SURF and ORB feature descriptors","volume":"82","author":"A Kaur","year":"2023","journal-title":"Multimed Tools Appl"},{"issue":"12","key":"pone.0344847.ref033","doi-asserted-by":"crossref","first-page":"12814","DOI":"10.1109\/TKDE.2023.3268069","article-title":"Multiplex graph representation learning via dual correlation reduction","volume":"35","author":"Y Mo","year":"2023","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"1","key":"pone.0344847.ref034","doi-asserted-by":"crossref","first-page":"506","DOI":"10.1109\/TCYB.2023.3256080","article-title":"Filter-Informed spectral graph wavelet networks for multiscale feature extraction and intelligent fault diagnosis","volume":"54","author":"T Li","year":"2024","journal-title":"IEEE Trans Cybern"},{"key":"pone.0344847.ref035","doi-asserted-by":"crossref","first-page":"3359","DOI":"10.1007\/s00170-025-15169-8","article-title":"Lithium-ion batteries remaining useful life prediction using a parallel BILSTM-MHA neural network based on a CEEMDAN module","volume":"137","author":"C Duan","year":"2025","journal-title":"Int J Adv Manuf Technol"},{"issue":"1","key":"pone.0344847.ref036","doi-asserted-by":"crossref","first-page":"1514","DOI":"10.1109\/TPEL.2023.3321762","article-title":"Open-circuit fault diagnosis in NPC rectifiers using reference voltage deviation and incorporating fault-tolerant control","volume":"39","author":"M Chen","year":"2024","journal-title":"IEEE Trans Power Electron"},{"issue":"2","key":"pone.0344847.ref037","doi-asserted-by":"crossref","first-page":"2409","DOI":"10.1021\/acsomega.3c06796","article-title":"Anomaly detection method for lithium-ion battery cells based on time series decomposition and improved manhattan distance algorithm","volume":"9","author":"M Wu","year":"2023","journal-title":"ACS Omega"},{"issue":"12","key":"pone.0344847.ref038","first-page":"2297","article-title":"Lithium-ion battery fault diagnosis method based on KPCA-MTCN","volume":"46","author":"Q Tan","year":"2024","journal-title":"Chinese Journal of Engineering"}],"container-title":["PLOS One"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0344847","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T17:24:54Z","timestamp":1773768294000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0344847"}},"subtitle":[],"editor":[{"given":"Shaheer","family":"Ansari","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2026,3,17]]},"references-count":38,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3,17]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0344847","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,17]]}}}