Article(id=1322622409987961121, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1322622385379983486, articleNumber=null, orderNo=null, doi=10.19620/j.cnki.1000-3703.20260005, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1787673600000, revisedDateStr=2026-08-26, acceptedDate=null, acceptedDateStr=null, onlineDate=1793267355676, onlineDateStr=2026-10-29, pubDate=1792771200000, pubDateStr=2026-10-24, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1793267355676, onlineIssueDateStr=2026-10-29, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1793267355676, creator=13701087609, updateTime=1793267355676, updator=13701087609, issue=Issue{id=1322622385379983486, tenantId=1146029695717560320, journalId=1189621681917173762, year='2026', volume='', issue='10', pageStart='1', pageEnd='62', issueExtLink='null', onlineDate='null', pubDate='1792771200000', pubDateStr='2026-10-24', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1793267349810, creator='13701087609', updateTime=1793268459387, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1322627039367123647, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1322622385379983486, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1322627039367123648, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1322622385379983486, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=54, endPage=62, ext={EN=ArticleExt(id=1322622410151538978, articleId=1322622409987961121, tenantId=1146029695717560320, journalId=1189621681917173762, language=EN, title=Optimization of Injection Strategy for Methanol/Diesel Dual-Direct-Injection Engine Based on RSM-NSGA-Ⅱ-EWTOPSIS, columnId=null, journalTitle=Automobile Technology, columnName=null, runingTitle=null, highlight=null, articleAbstract=

To address the problem of synergistic optimization of injection parameters in the double diesel injection strategy for a methanol-diesel dual-direct injection engine, a hybrid multi-objective optimization approach coupling Response Surface Methodology, Non-Dominated Sorting Genetic Algorithm and Technique for Order Preference by Similarity to Ideal Solution with Entropy Weighted (RSM-NSGA-Ⅱ-EWTOPSIS) was employed to optimize the timing of the first diesel injection (θ_D1), the first injection energy ratio (R_D1), and the interval time between injections (I_D) in this study. Under medium load conditions at 2 000 r/min, the optimal injection parameter combination was obtained as θ_D1 = -38.9 °CA ATDC, R_D1 = 43.8%, and I_D = 16.8 °CA. Compared to the initial strategy (θ_D1 = -29 °CA ATDC, R_D1 = 43.1%, I_D = 12 °CA), peak cylinder pressure increased by 7.72% after optimization, combustion phase advanced, and the heat release process became more concentrated. Concurrently, the indicated thermal efficiency improved by 1.06%, while the emissions of NO_x and CO decreased by 9.55% and 10.4%, respectively. The results demonstrate that the proposed optimized injection strategy achieves synergistic improvements in thermal efficiency and pollutant reduction.

, authors=Manyao Xie, Ying Wang, Da Zhang, authorsList=Manyao Xie, Ying Wang, Da Zhang, authorCompany=null, correspAuthors=Ying Wang, 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=1322622410407391523, articleId=1322622409987961121, tenantId=1146029695717560320, journalId=1189621681917173762, language=CN, title=基于RSM-NSGA-Ⅱ-EWTOPSIS的甲醇/柴油双直喷发动机喷射策略优化, columnId=0, journalTitle=汽车技术, columnName=, runingTitle=null, highlight=null, articleAbstract=

针对甲醇-柴油双直喷发动机柴油2次喷射策略中喷射参数的协同优化问题，本文采用响应面法-非支配排序遗传算法-熵权逼近理想解排序法（RSM-NSGA-Ⅱ-EWTOPSIS）相结合的多目标优化方法，对柴油第一次喷射时刻θ_D1、第1次喷射能量占比R_D1以及两次喷射间隔I_D进行了优化研究。在转速2 000 r/min、中等负荷工况下，获得最优喷射参数组合为θ_D1= -38.9 °CA ATDC、R_D1 = 43.8%、I_D = 16.8 °CA。与初始策略（θ_D1 = -29 °CA ATDC、R_D1 = 43.1%、I_D = 12 °CA）相比，优化后缸压峰值提升7.72%，燃烧相位提前，放热过程更为集中。同时，指示热效率提高1.06%，NO_x和CO排放量分别降低9.55%与10.4%。结果表明，所提出的优化喷射策略可实现热效率提升及NO_x与CO的协同改善。

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