Article(id=1322531344324875075, tenantId=1146029695717560320, journalId=1146031654075715584, issueId=1322531228222337541, articleNumber=null, orderNo=null, doi=10.13234/j.issn.2095-2805.2026.3.170, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1682438400000, receivedDateStr=2023-04-26, revisedDate=1697472000000, revisedDateStr=2023-10-17, acceptedDate=1701446400000, acceptedDateStr=2023-12-02, onlineDate=1793245643930, onlineDateStr=2026-10-29, pubDate=1774800000000, pubDateStr=2026-03-30, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793245643930, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793245643930, creator=13701087609, updateTime=1793245643930, updator=13701087609, issue=Issue{id=1322531228222337541, tenantId=1146029695717560320, journalId=1146031654075715584, year='2026', volume='24', issue='3', pageStart='1', pageEnd='343', issueExtLink='null', onlineDate='null', pubDate='1774800000000', pubDateStr='2026-03-30', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1793245616250, creator='13701087609', updateTime=1793245616250, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=170, endPage=177, ext={EN=ArticleExt(id=1322531344509424452, articleId=1322531344324875075, tenantId=1146029695717560320, journalId=1146031654075715584, language=EN, title=PDF Feature Extraction and SOH Estimation for Energy Storage Lithium-ion Batteries with Noise Immunity, columnId=1321491614980223555, journalTitle=Journal of Power Supply, columnName=Renewable Energy Generation and Energy Storage, runingTitle=null, highlight=null, articleAbstract=

The analysis method based on incremental capacity (IC) achieves effective analysis of the aging mechanism of lithium-ion batteries by converting voltage plateaus into characteristic peaks. However, the immune capability of IC curves with respect to noise is poor, and the extracted health features are susceptible to interference from the noise peaks. To solve this problem, a state-of-health (SOH) estimation method based on noise immunity probability density function (PDF) feature extraction combined with an ensemble learning model is proposed. First, the PDF curve is obtained by calculating the PDF of the voltage curve, and different peak features extracted from the PDF and IC curves are analyzed and compared by setting different values of signal-to-noise ratio. Second, the learning speed and randomness of extreme learning machine are used to construct an ensemble learning model framework, so as to reduce the prediction error of a single model. Finally, SOH estimation experiments under different noise conditions were conducted on the CALCE dataset, and results demonstrated the high accuracy and reliability of the proposed method.

, authors=Yong YANG¹, Haobin ZHU², Jingwu ZHU¹, Jing GE², Dan ZHU², authorsList=Yong YANG, Haobin ZHU, Jingwu ZHU, Jing GE, Dan ZHU, authorCompany=null, correspAuthors=Yong YANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1322531344790442821, articleId=1322531344324875075, tenantId=1146029695717560320, journalId=1146031654075715584, language=CN, title=具有抗噪声干扰的储能锂离子电池PDF特征提取及SOH估计, columnId=1321491615269630533, journalTitle=电源学报, columnName=新能源发电与储能, runingTitle=null, highlight=null, articleAbstract=

基于增量容量IC（incremental capacity）的分析方法通过将电压平台转换为特征峰，实现了对锂离子电池老化机制的有效解析。然而，IC曲线对噪声的免疫能力较差，其提取的健康特征易受到噪声峰的干扰。为解决此问题，结合集成学习模型提出1种基于抗噪声干扰的概率密度函数PDF（probability density function）特征提取的健康状态SOH（state-of-health）估计方法。首先，通过对电压曲线计算概率密度函数得到PDF曲线，然后通过设置不同信噪比对PDF和IC曲线提取的不同峰特征进行分析对比。其次，利用极限学习机的学习速度和随机性，构建集成学习模型框架来降低单一模型的预测误差。最后，在CALCE数据集上进行了不同噪声条件下的SOH估计实验，证明了该方法具有较高的精度和可靠性。

, authors=杨勇¹, 朱皓斌², 朱精武¹, 葛景², 朱丹², authorsList=杨勇, 朱皓斌, 朱精武, 葛景, 朱丹, authorCompany=null, correspAuthors=杨勇, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=hLJPuGiCS/gRUg0fpCC6Ng==, magXml=+XR7M1kFbfRNp0UZT6OK9w==, pdfUrl=null, pdf=qM+NGNSemKTTiRo6kOC77w==, pdfFileSize=2603363, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=Two+w8C6I+P2kB/d7tOVDQ==, mapNumber=null, fund=null)}, authors=[Author(id=1322531437891404477, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=yangyong_407@163.com, emailSecond=null, emailThird=null, correspondingAuthor=1, authorType=1, ext={EN=AuthorExt(id=1322531437962707647, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, authorId=1322531437891404477, language=EN, stringName=Yong YANG, firstName=Yong, middleName=null, lastName=YANG, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.Inner Mongolia Power (Group) Co., Ltd., Hohhot 010000, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1322531438218560192, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, authorId=1322531437891404477, language=CN, stringName=杨勇, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=^1.内蒙古电力（集团）有限责任公司，呼和浩特　010000, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null)}, companyList=[AuthorCompany(id=1322531437660717750, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, xref=1., ext=[AuthorCompanyExt(id=1322531437669106359, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, companyId=1322531437660717750, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=^1.Inner Mongolia Power (Group) Co., Ltd., Hohhot 010000, China), AuthorCompanyExt(id=1322531437677494968, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, companyId=1322531437660717750, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=^1.内蒙古电力（集团）有限责任公司，呼和浩特　010000)])]), Author(id=1322531438281474754, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, orderNo=1, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=zhuhaobin@nrec.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1322531438365360836, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, authorId=1322531438281474754, language=EN, stringName=Haobin ZHU, firstName=Haobin, middleName=null, lastName=ZHU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=², address=^2.Nanjing Nanrui Jibao Engineering Technology Co., Ltd., Nanjing 211102, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1322531438432469701, tenantId=1146029695717560320, journalId=1146031654075715584, articleId=1322531344324875075, authorId=1322531438281474754, language=CN, stringName=朱皓斌, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=², address=^2.南京南瑞继保工程技术有限公司，南京　211102, bio={"content":"

朱皓斌（1987—　），男，硕士，高级工程师。研究方向：微电网控制与保护技术。E-mail：zhuhaobin@nrec.com。

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朱皓斌（1987—　），男，硕士，高级工程师。研究方向：微电网控制与保护技术。E-mail：zhuhaobin@nrec.com。

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朱精武（1990—　），男，本科，工程师。研究方向：电网规划建设。E-mail：18804876644@163.com。

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朱精武（1990—　），男，本科，工程师。研究方向：电网规划建设。E-mail：18804876644@163.com。

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葛景（1992—　），男，硕士，工程师。研究方向：高比例新能源电网系统分析。E-mail：gejing@nrec.com。

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葛景（1992—　），男，硕士，工程师。研究方向：高比例新能源电网系统分析。E-mail：gejing@nrec.com。

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朱丹（1987—　），男，硕士，高级工程师。研究方向：微电网控制与保护技术。E-mail：zhud@nrec.com。

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朱丹（1987—　），男，硕士，高级工程师。研究方向：微电网控制与保护技术。E-mail：zhud@nrec.com。

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