{"title":"锂离子电池的单粒子模型 - 模型校准和电动汽车应用中真实数据的验证⁎","authors":"Iulian Munteanu , Antoneta Iuliana Bratcu , Pierre-Xavier Thivel , Yann Bultel , Didier Georges , Céline Decaux","doi":"10.1016/j.ifacol.2024.07.454","DOIUrl":null,"url":null,"abstract":"<div><p>This paper investigates the problem of calibration and validation of a battery electrochemical model as a mandatory step towards accurate estimation of battery important variables, like state of charge (SoC) and state of health (SoH). Here, the Single Particle Model (SPM) is considered, which mathematically describes the battery internal governing phenomena by means of parabolic partial differential equations (PDEs), but whose parameters are notoriously difficult to measure or estimate. After suitable approximation of this model through a linear finite-dimensional model, a systematic procedure of SPM calibration is here proposed and validated against real data issued from battery cycling in an electric vehicular application, i.e., under standard driving cycle scenarios. In a novel approach of SoC estimation, the suitably calibrated SPM, together with measures of voltage and current, allow to analytically connect the internal spatially distributed ions’ concentrations to the equilibrium concentration, which, at its turn, is an image of battery SoC. Results suggest that SPM can reliably predict the battery internal ions’ concentrations and be further used for SoC accurate estimation.</p></div>","PeriodicalId":37894,"journal":{"name":"IFAC-PapersOnLine","volume":"58 13","pages":"Pages 23-30"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2405896324005536/pdf?md5=8506a41a226fd7fd5de3e0f3a8fc5ac9&pid=1-s2.0-S2405896324005536-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Single-Particle Model of Li-ion Battery – Model Calibration and Validation against Real Data in an Electric Vehicular Application⁎\",\"authors\":\"Iulian Munteanu , Antoneta Iuliana Bratcu , Pierre-Xavier Thivel , Yann Bultel , Didier Georges , Céline Decaux\",\"doi\":\"10.1016/j.ifacol.2024.07.454\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper investigates the problem of calibration and validation of a battery electrochemical model as a mandatory step towards accurate estimation of battery important variables, like state of charge (SoC) and state of health (SoH). Here, the Single Particle Model (SPM) is considered, which mathematically describes the battery internal governing phenomena by means of parabolic partial differential equations (PDEs), but whose parameters are notoriously difficult to measure or estimate. After suitable approximation of this model through a linear finite-dimensional model, a systematic procedure of SPM calibration is here proposed and validated against real data issued from battery cycling in an electric vehicular application, i.e., under standard driving cycle scenarios. In a novel approach of SoC estimation, the suitably calibrated SPM, together with measures of voltage and current, allow to analytically connect the internal spatially distributed ions’ concentrations to the equilibrium concentration, which, at its turn, is an image of battery SoC. Results suggest that SPM can reliably predict the battery internal ions’ concentrations and be further used for SoC accurate estimation.</p></div>\",\"PeriodicalId\":37894,\"journal\":{\"name\":\"IFAC-PapersOnLine\",\"volume\":\"58 13\",\"pages\":\"Pages 23-30\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2405896324005536/pdf?md5=8506a41a226fd7fd5de3e0f3a8fc5ac9&pid=1-s2.0-S2405896324005536-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IFAC-PapersOnLine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2405896324005536\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IFAC-PapersOnLine","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405896324005536","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
Single-Particle Model of Li-ion Battery – Model Calibration and Validation against Real Data in an Electric Vehicular Application⁎
This paper investigates the problem of calibration and validation of a battery electrochemical model as a mandatory step towards accurate estimation of battery important variables, like state of charge (SoC) and state of health (SoH). Here, the Single Particle Model (SPM) is considered, which mathematically describes the battery internal governing phenomena by means of parabolic partial differential equations (PDEs), but whose parameters are notoriously difficult to measure or estimate. After suitable approximation of this model through a linear finite-dimensional model, a systematic procedure of SPM calibration is here proposed and validated against real data issued from battery cycling in an electric vehicular application, i.e., under standard driving cycle scenarios. In a novel approach of SoC estimation, the suitably calibrated SPM, together with measures of voltage and current, allow to analytically connect the internal spatially distributed ions’ concentrations to the equilibrium concentration, which, at its turn, is an image of battery SoC. Results suggest that SPM can reliably predict the battery internal ions’ concentrations and be further used for SoC accurate estimation.
期刊介绍:
All papers from IFAC meetings are published, in partnership with Elsevier, the IFAC Publisher, in theIFAC-PapersOnLine proceedings series hosted at the ScienceDirect web service. This series includes papers previously published in the IFAC website.The main features of the IFAC-PapersOnLine series are: -Online archive including papers from IFAC Symposia, Congresses, Conferences, and most Workshops. -All papers accepted at the meeting are published in PDF format - searchable and citable. -All papers published on the web site can be cited using the IFAC PapersOnLine ISSN and the individual paper DOI (Digital Object Identifier). The site is Open Access in nature - no charge is made to individuals for reading or downloading. Copyright of all papers belongs to IFAC and must be referenced if derivative journal papers are produced from the conference papers. All papers published in IFAC-PapersOnLine have undergone a peer review selection process according to the IFAC rules.