Article(id=1308462973316522039, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462963522823142, articleNumber=null, orderNo=null, doi=10.20104/j.cnki.1674-6546.20260024, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1773072000000, revisedDateStr=2026-03-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1789891482904, onlineDateStr=2026-09-20, pubDate=1784044800000, pubDateStr=2026-07-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1789891482904, onlineIssueDateStr=2026-09-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1789891482904, creator=13701087609, updateTime=1789891482904, updator=13701087609, issue=Issue{id=1308462963522823142, tenantId=1146029695717560320, journalId=1189918454225211397, year='2026', volume='', issue='7', pageStart='1', pageEnd='48', issueExtLink='null', onlineDate='null', pubDate='1784044800000', pubDateStr='2026-07-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1789891480570, creator='13701087609', updateTime=1789892910062, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1308468959309751193, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462963522823142, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1308468959309751194, tenantId=1146029695717560320, journalId=1189918454225211397, issueId=1308462963522823142, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=44, endPage=48, ext={EN=ArticleExt(id=1308462973475905592, articleId=1308462973316522039, tenantId=1146029695717560320, journalId=1189918454225211397, language=EN, title=Research on Fuel Economy of Heavy-Duty Trucks Based on Predictive Adaptive Cruise Control, columnId=null, journalTitle=Automotive Engineer, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address the issue of high fuel consumption in heavy-duty truck druing hill-climing conditions, a fuel comsumption predicton model balancing accuracy and real-time performance is developed by inregrating parameters such as engine speed and torque. This paper proposes a fuel-saving strategy for heavy trucks using Predictive Adaptive Cruise Control (PACC) on sloped roads. A hierarchical architecture is developed: the upper layer employs Dynamic Programming (DP) for global economic speed planning, while the lower layer uses Model Predictive Control (MPC) for secondary planning to ensure safe following and energy efficiency. A fuel consumption model considering engine torque and speed is integrated. Vehicle test demonstrates an average fuel reduction of 1.5% per kilometer.

, authors=Kaihua Ye¹, Jun Li², Jianbin Huang³, Tao Tang³, authorsList=Kaihua Ye, Jun Li, Jianbin Huang, Tao Tang, authorCompany=null, correspAuthors=Jun Li, 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=1308462973710786617, articleId=1308462973316522039, tenantId=1146029695717560320, journalId=1189918454225211397, language=CN, title=基于预见性自适应巡航控制的重型载货汽车燃油经济性优化研究, columnId=0, journalTitle=汽车工程师, columnName=, runingTitle=null, highlight=null, articleAbstract=

针对重型载货汽车在爬坡工况下燃油消耗量大的问题，综合发动机转速、扭矩等参数建立了兼顾精度与实时性的燃油消耗量预测模型，并提出一种基于预见性自适应巡航控制（PACC）的分层架构：上层利用动态规划（DP）算法规划全局最优经济车速；下层基于模型预测控制（MPC）算法进行二次速度规划，在确保安全跟车的同时进一步提高经济性。实车试验结果表明，该方法可使载货汽车燃油消耗量平均降低1.5%。

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