Article(id=1282029987217781054, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2025.07.0708, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1742745600000, receivedDateStr=2025-03-24, revisedDate=1747324800000, revisedDateStr=2025-05-16, acceptedDate=null, acceptedDateStr=null, onlineDate=1783589367918, onlineDateStr=2026-07-09, pubDate=1753632000000, pubDateStr=2025-07-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783589367918, onlineIssueDateStr=2026-07-09, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783589367918, creator=13701087609, updateTime=1783589367918, updator=13701087609, issue=Issue{id=1282029960869167928, tenantId=1146029695717560320, journalId=1146031787341344770, year='2025', volume='35', issue='7', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='1753632000000', pubDateStr='2025-07-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783589361636, creator='13701087609', updateTime=1783589710614, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282031424651903975, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282031424656098280, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1282029960869167928, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=184, endPage=191, ext={EN=ArticleExt(id=1282029987402330431, articleId=1282029987217781054, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Active online multi-source monitoring and hierarchical early warning system for LiFePO₄ energy storage power station, columnId=1149733269173878863, journalTitle=China Safety Science Journal, columnName=Safety engineering technology, runingTitle=null, highlight=null, articleAbstract=

In order to enhance the accident monitoring effect and early warning efficiency of lithium-ion battery energy storage power stations and reduce the probability of fire occurrence, aiming at the problems existing in prefabricated cabin LiFePO₄ (LFP) battery energy storage power stations, such as passive monitoring delay, inaccurate monitoring of a single parameter, and ambiguous classification of disaster risks, an active online multi-source monitoring and hierarchical early warning system for LFP energy storage power stations was designed. Firstly, the thermal runaway and fire occurrence process of the energy storage power station was analyzed. The characteristic index set of each level was constructed, which is specific: internal temperature (single), internal pressure-sound (battery Pack), H₂ and CO concentration (battery cluster), smoke characteristic image (battery chamber), and plan a detailed monitoring implementation path. Then, based on the four-level early warning corresponding to the four levels, formulate the early warning strategy and clarify the early warning process. Experimental results demonstrated that: This monitoring and early warning system can effectively achieve the early warning of LFP energy storage power stations. Under 2C overcharging conditions, it can give an early warning of the thermal runaway of 32 Ah battery cells 38.9 min in advance. The combustion of the 344 Ah battery module was warned 53.2 min in advance under the condition of 0.5C overcharging. This study proves that this system can provide an effective guarantee for the safe operation of energy storage power stations.

, authors=Qingqing XU¹, Jie CHEN^{**, 1}, Baobin GAO¹, Yan WANG¹, Jian WANG¹, Zutian CHENG², authorsList=Qingqing XU, Jie CHEN, Baobin GAO, Yan WANG, Jian WANG, Zutian CHENG, authorCompany=null, correspAuthors=Jie CHEN, 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=1282029987855315266, articleId=1282029987217781054, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=磷酸铁锂储能电站主动在线多源监测和分级预警系统, columnId=1149733269727526997, journalTitle=中国安全科学学报, columnName=安全工程技术, runingTitle=null, highlight=null, articleAbstract=

为提升锂离子电池储能电站事故监测效果和预警效率，降低火灾发生概率，针对预制舱式磷酸铁锂（LFP）电池储能电站存在的被动监测延时、单一参量监测不准确以及灾变风险分级模糊等问题，设计一套LFP储能电站主动在线多源监测与分级预警系统。首先，分析储能电站热失控及火灾发生过程，基于不同层级构建特征指标集，包括内部温度（单体）、内压-声音（电池包）、H₂和CO浓度（电池簇）、烟雾特征图像（电池舱），并规划详细的监测实施路径；然后，根据4个层级对应的4级预警，制定预警策略，明确预警流程。结果表明：该监测预警系统在LFP储能电站热失控极早期预警方面有显著优势，尤其是在2C过充条件下，可提前38.9 min预警32 Ah电池单体的热失控；在0.5C过充条件下提前53.2 min预警344 Ah电池模组的燃烧。

, authors=许晴晴¹, 陈杰讲师^{**, 1}, 高保彬教授¹, 王燕教授¹, 王健副教授¹, 程祖田高级工程师², authorsList=许晴晴, 陈杰讲师, 高保彬教授, 王燕教授, 王健副教授, 程祖田高级工程师, authorCompany=null, correspAuthors=陈杰讲师, authorNote=, correspAuthorsNote=, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=Y6KfcyzJxnEtgm4k41OmXA==, magXml=JSVtpns9h/UGmLe0p3BT5g==, pdfUrl=null, pdf=9IcGU+g+3cIPtNEdlSBJmA==, pdfFileSize=7858691, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=zofPeZnhAS1mGcvdUkhuwA==, mapNumber=null, fund=null)}, authors=[Author(id=1282029988295717194, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282029987217781054, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=13782830668@163.com, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1282029988379603276, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282029987217781054, authorId=1282029988295717194, language=EN, stringName=Qingqing XU, firstName=Qingqing, middleName=null, lastName=XU, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹School of Safety Science and Engineering, Henan Polytechnic University, Jiaozuo Henan 454003, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1282029988442517837, tenantId=1146029695717560320, journalId=1146031787341344770, articleId=1282029987217781054, authorId=1282029988295717194, language=CN, stringName=许晴晴, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=¹, address=¹河南理工大学 安全科学与工程学院，河南 焦作 454003, bio={"content":"

许晴晴（2000—），女，河南焦作人，硕士研究生，主要研究方向为电化学储能电站的安全理论与技术。E-mail:13782830668@163.com。

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许晴晴（2000—），女，河南焦作人，硕士研究生，主要研究方向为电化学储能电站的安全理论与技术。E-mail:13782830668@163.com。

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