Article(id=1308462937874657817, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462937421672985, articleNumber=null, orderNo=null, doi=10.20104/j.cnki.1674-6546.20250210, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1755792000000, revisedDateStr=2025-08-22, acceptedDate=null, acceptedDateStr=null, onlineDate=1789891474455, onlineDateStr=2026-09-20, pubDate=1786723200000, pubDateStr=2026-08-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789891474455, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789891474455, creator=13701087609, updateTime=1789891474455, updator=13701087609, issue=Issue{id=1308462937421672985, tenantId=1146029695717560320, journalId=1189918454225211397, year='2026', volume='', issue='8', pageStart='1', pageEnd='48', issueExtLink='null', onlineDate='null', pubDate='1786723200000', pubDateStr='2026-08-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789891474347, creator='13701087609', updateTime=1789892927625, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308469032970118051, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462937421672985, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308469032970118052, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462937421672985, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=12, ext={EN=ArticleExt(id=1308462938071790106, articleId=1308462937874657817, tenantId=1146029695717560320, journalId=1189918454225211397, language=EN, title=Research Progress on the Application of Electronic Nose in Vehicle Odorant Detection, columnId=null, journalTitle=Automotive Engineer, columnName=null, runingTitle=null, highlight=null, articleAbstract=

Electronic nose technology holds immense application potential for odorants and air quality control within vehicles, owing to its significant advantages of high sensitivity, operational convenience and low cost. This paper focuses on the application of electronic nose technology in the identification and classification of gas components, with a particular emphasis on the working principles of electronic nose technology, the response performance of various gas sensors and pattern recognition algorithms. Additionally, the paper discusses the progress made in the use of electronic nose technology for Indoor Air Quality (IAQ) evaluation and the identification of odorants emitted by whole vehicles or interior materials. Finally, the paper provides an outlook on the future development direction and challenges of electronic nose technology in the field of vehicle odorant detection.

, authors=Jiqin Zhong¹, Bo Li¹, Mingyi Li¹, Xiaojin Zhao², Xiaofang Pan², authorsList=Jiqin Zhong, Bo Li, Mingyi Li, Xiaojin Zhao, Xiaofang Pan, authorCompany=null, correspAuthors=null, 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=1308462938273116699, articleId=1308462937874657817, tenantId=1146029695717560320, journalId=1189918454225211397, language=CN, title=电子鼻在车内气味物质识别中的应用研究进展, columnId=0, journalTitle=汽车工程师, columnName=, runingTitle=null, highlight=null, articleAbstract=

电子鼻技术因其识别灵敏度高、操作便捷和成本低等显著优势而在车内气味物质识别和空气质量管控领域表现出巨大的应用潜力。基于电子鼻技术在气体组分识别与分类中的应用，阐述了电子鼻技术的工作原理、各类气体传感器的响应性能，以及模式识别算法模型等方面的相关研究工作，重点分析了电子鼻技术在车内空气质量（IAQ）评价及整车/内饰材料散发的气味物质识别应用方面的研究进展，最后对电子鼻在车内气味物质识别领域的未来发展方向与挑战进行了展望。

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