Article(id=1242140926408209252, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242140911858163906, articleNumber=null, orderNo=null, doi=10.3981/j.issn.1000-7857.2024.02.008, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1652803200000, receivedDateStr=2022-05-18, revisedDate=1690646400000, revisedDateStr=2023-07-30, acceptedDate=null, acceptedDateStr=null, onlineDate=1713110400000, onlineDateStr=2024-04-15, pubDate=1706371200000, pubDateStr=2024-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1713110400000, onlineIssueDateStr=2024-04-15, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774079074715, creator=sys-migrate, updateTime=1774079074715, updator=sys-migrate, issue=Issue{id=1242140911858163906, tenantId=1146029695717560320, journalId=1146031591421210625, year='2024', volume='42', issue='2', pageStart='1', pageEnd='128', issueExtLink='null', onlineDate='null', pubDate='1706371200000', pubDateStr='2024-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=null, issueType=-1, specialIssue=null, createTime=1774079071246, creator='sys-migrate', updateTime=1774079071246, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=79, endPage=89, ext={EN=ArticleExt(id=1242140932808712487, articleId=1242140926408209252, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Review of battery life prediction and energy control management strategies for hybrid electric vehicles, columnId=1242116810380743325, journalTitle=Science & Technology Review, columnName=Reviews, runingTitle=null, highlight=null, articleAbstract=At present, environmental pollution and energy shortage are becoming increasingly serious, and the automobile industry is also moving in the direction of energy conservation and environmental protection. In order to promote the research on the power performance and fuel economy of hybrid electric vehicles, this paper briefly analyzes the working principle of the lithium-ion battery and the factors affecting the life of the lithium-ion battery, summarizes the research status of different methods for predicting the remaining life of the lithium-ion battery and analyzes their advantages and disadvantages. According to the working mode of hybrid electric vehicles, the working mechanism of energy control management strategies are briefly explained, and the development status of energy control management strategies based on rules, optimization and artificial intelligence is described respectively. The influence of battery life control management strategy on vehicle economic performance is discussed. According to the relevant literature analysis, it is found that the battery life prediction method combining multiple methods is more superior, and the energy control management strategy considering battery life has a better effect on improving the fuel economy of hybrid electric vehicles. The problems of battery life prediction and energy control management strategies for hybrid electric vehicles are summarized and the future development direction is forecasted., authors=WU Xudong¹, WANG Jingyue^1,2, XUE Chunwei¹, ZHENG Junwen¹, LEI Hu¹, WANG Junnian², authorsList=WU Xudong, WANG Jingyue, XUE Chunwei, ZHENG Junwen, LEI Hu, WANG Junnian, authorCompany=1. School of Automobile and Transportation, Shenyang Ligong University, Shenyang 110159, China;
2. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130025, China, 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=1242140930950635807, articleId=1242140926408209252, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=混合动力汽车电池寿命预测及能量控制管理策略, columnId=1242134377686180284, journalTitle=科技导报, columnName=综述, runingTitle=null, highlight=null, articleAbstract=针对混合动力汽车电池寿命预测及能量管理，分析了锂离子电池工作原理及影响寿命的因素，综述了不同锂离子电池剩余寿命预测方法的研究状况，并讨论了各种方法的优缺点；依据混合动力汽车工作模式简要说明能量控制策略工作机理，分别论述了基于规则、基于优化及基于人工智能等能量控制管理策略的发展现状，讨论了考虑电池寿命的控制策略对整车经济性能的影响。分析发现，融合多种方法的电池寿命预测方法更具优越性，且考虑电池寿命的能量控制管理策略对混合动力汽车燃油经济性的提高效果更佳。总结了混合动力汽车电池寿命预测及能量控制管理策略存在的问题并对未来的发展方向进行展望。, authors=武旭东¹, 王靖岳^1,2, 薛春伟¹, 郑珺文¹, 雷虎¹, 王军年², authorsList=武旭东, 王靖岳, 薛春伟, 郑珺文, 雷虎, 王军年, authorCompany=1. 沈阳理工大学汽车与交通学院, 沈阳 110159;
2. 吉林大学汽车仿真与控制国家重点实验室, 长春 130025, correspAuthors=null, authorNote=武旭东，硕士研究生，研究方向为新能源汽车技术，电子信箱：1294756694@qq.com, correspAuthorsNote=王靖岳（通信作者），教授，研究方向为车辆系统动力学与控制，电子信箱：abswell@126.com, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=1dGPBzfvPZkupbcFmYP+gw==, pdfFileSize=2283546, 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=汽车仿真与控制国家重点实验室开放基金项目（20191203）；辽宁省自然科学基金项目（2020-MS-216）)}, authors=null, keywords=[Keyword(id=1242140930560565531, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242140926408209252, language=CN, orderNo=1, keyword=混合动力汽车), Keyword(id=1242140930640257308, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1242140926408209252, language=CN, orderNo=1, keyword=锂离子电池), 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