A Novel Dual Particle Filter - Based Approach for Joint Online Estimation of State of Charge and State of Health in Lithium-ion Battery Packs

A Novel Dual Particle Filter - Based Approach for Joint Online Estimation of State of Charge and State of Health in Lithium-ion Battery Packs | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Novel Dual Particle Filter - Based Approach for Joint Online Estimation of State of Charge and State of Health in Lithium-ion Battery Packs Nana Zhou, Lianfeng Lai, Zhihui Deng, Fengjun Zhou, Bing Lu, Weiwei Huo, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9342981/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract This study establishes equivalent circuit models for battery packs with four distinct connection methods: series connection, parallel connection, series-parallel connection, and parallel-series connection. A dual particle filter (DPF) algorithm is employed to jointly estimate the state of charge (SOC) and state of health, with the aim of exploring the performance differences among them. Given that the initial value has a substantial impact on the estimation accuracy of the DPF algorithm, the particle swarm optimization algorithm (PSO) is utilized to optimize the initial value of the DPF, thereby enhancing its estimation performance. To validate the accuracy of the SOC estimation, dynamic stress test (DST) working conditions are adopted. The performance of the DPF algorithm is compared with that of the dual extended Kalman filter (DEKF) and extended Kalman filter (EKF) algorithms. The results unequivocally demonstrate that the DPF algorithm outperforms the DEKF and EKF algorithms in terms of SOC estimation accuracy. Specifically, for the four different battery packs, the root mean square error and mean absolute error) of the SOC estimation using the DPF algorithm are all below 2%. This indicates that the DPF algorithm exhibits high estimation accuracy and robustness, providing a valuable reference for lithium-ion battery packs. Physical sciences/Energy science and technology Physical sciences/Engineering Physical sciences/Mathematics and computing battery pack state of charge health state joint estimation dual particle filter Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 29 Apr, 2026 Reviews received at journal 28 Apr, 2026 Reviews received at journal 24 Apr, 2026 Reviewers agreed at journal 24 Apr, 2026 Reviewers agreed at journal 21 Apr, 2026 Reviewers invited by journal 21 Apr, 2026 Editor assigned by journal 21 Apr, 2026 Editor invited by journal 21 Apr, 2026 Submission checks completed at journal 15 Apr, 2026 First submitted to journal 15 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9342981","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":630877871,"identity":"5bce16a2-45e8-4a52-81b7-0e9f2a03ae94","order_by":0,"name":"Nana Zhou","email":"","orcid":"","institution":"Shandong Xiehe University","correspondingAuthor":false,"prefix":"","firstName":"Nana","middleName":"","lastName":"Zhou","suffix":""},{"id":630877872,"identity":"1b88ebbe-1aa5-47f5-b821-cc7569ec82f9","order_by":1,"name":"Lianfeng Lai","email":"","orcid":"","institution":"Ningde Normal University","correspondingAuthor":false,"prefix":"","firstName":"Lianfeng","middleName":"","lastName":"Lai","suffix":""},{"id":630877873,"identity":"1b790869-cd85-4571-b92b-08507f1c0d9f","order_by":2,"name":"Zhihui Deng","email":"","orcid":"","institution":"Ningde Normal University","correspondingAuthor":false,"prefix":"","firstName":"Zhihui","middleName":"","lastName":"Deng","suffix":""},{"id":630877874,"identity":"33ef730d-1eb6-4f33-90ec-3152ae35c712","order_by":3,"name":"Fengjun Zhou","email":"","orcid":"","institution":"Shandong Xiehe University","correspondingAuthor":false,"prefix":"","firstName":"Fengjun","middleName":"","lastName":"Zhou","suffix":""},{"id":630877877,"identity":"7775f9c9-25ef-4084-b676-c894e80284d6","order_by":4,"name":"Bing Lu","email":"","orcid":"","institution":"Beijing Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Bing","middleName":"","lastName":"Lu","suffix":""},{"id":630877879,"identity":"709d507d-9851-4011-8bb9-804d4a9e214a","order_by":5,"name":"Weiwei Huo","email":"","orcid":"","institution":"Beijing Information Science \u0026 Technology University","correspondingAuthor":false,"prefix":"","firstName":"Weiwei","middleName":"","lastName":"Huo","suffix":""},{"id":630877881,"identity":"3736cd4c-fbe4-4f24-94cc-aeb49aa090f9","order_by":6,"name":"Yonghong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA30lEQVRIie2POwrCQBRFnwwkzYiWCULW8GTADwTXMiEw1RgENyDYZgG6C6vUkUGzhfSClUXsLAR/SUonpBOc07xb3MPjAhgMPwmtrg0cCvS9FgoB3tksBGulAKGFChoFzOf74ip9b0zgPPCRcLDVYadT3E0UuttEsOkaQibRioAKkeuUniNHpJuoYKcgOEmkS3DoSKtYpfJ4K1xN0AlWTUr1JS2/AGKz4sYX9toSMlQQDmPkzGragpkcFtdk5mEWC+d2f3g9Wx21CvR5nWiZLG39Myatk51+bxkMBsNf8wTONUViZmLAOAAAAABJRU5ErkJggg==","orcid":"","institution":"Beijing Information Science \u0026 Technology University","correspondingAuthor":true,"prefix":"","firstName":"Yonghong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2026-04-07 09:54:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9342981/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9342981/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182974,"identity":"983a0363-1e88-4703-9a43-5a9c1096088b","added_by":"auto","created_at":"2026-04-30 08:59:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10186562,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9342981/v1_covered_7a58e931-7a79-455f-9320-129ba4ce4b46.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Novel Dual Particle Filter - 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