Article(id=1319244969513173960, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1319244966216446015, articleNumber=null, orderNo=null, doi=10.19620/j.cnki.1000-3703.20250594, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=null, receivedDateStr=null, revisedDate=1759939200000, revisedDateStr=2025-10-09, acceptedDate=null, acceptedDateStr=null, onlineDate=1792462111117, onlineDateStr=2026-10-20, pubDate=1790179200000, pubDateStr=2026-09-24, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1792462111117, onlineIssueDateStr=2026-10-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1792462111117, creator=13701087609, updateTime=1792462111117, updator=13701087609, issue=Issue{id=1319244966216446015, tenantId=1146029695717560320, journalId=1189621681917173762, year='2026', volume='', issue='9', pageStart='1', pageEnd='62', issueExtLink='null', onlineDate='null', pubDate='1790179200000', pubDateStr='2026-09-24', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1792462110332, creator='13701087609', updateTime=1792735854454, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1320393132613681559, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1319244966216446015, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1320393132613681560, tenantId=1146029695717560320, journalId=1189621681917173762, issueId=1319244966216446015, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=1, endPage=8, ext={EN=ArticleExt(id=1319244969777415113, articleId=1319244969513173960, tenantId=1146029695717560320, journalId=1189621681917173762, language=EN, title=Active Steering Stability Control of Steer-by-Wire Vehicles Using an Improved Adaptive Sliding Mode Control Approach, columnId=1319244967055306816, journalTitle=Automobile Technology, columnName=Special Topic on Lateral Stability and Motion Tracking Control Technology for Steer-by-Wire Vehicles, runingTitle=null, highlight=null, articleAbstract=

To enhance the handling stability and active safety of Steering-By-Wire (SBW) vehicles, this study proposes a stability control strategy based on sliding mode control, integrating yaw rate and sideslip angle as feedback variables on the foundation of variable steering ratio control. A Particle Swarm Optimization-Grey Wolf Optimization (PSO-GWO) algorithm is applied to optimize the variable steering ratio with constant yaw rate gain, ensuring high sensitivity at low speeds and stability at high speeds. In addition, an adaptive global fast terminal sliding mode controller is developed to suppress chattering, which generates an auxiliary front-wheel steering angle to further improve vehicle stability. The SBW system is modeled in MATLAB/Simulink and co-simulated with CarSim under double lane-change maneuvers on high-speed/high-friction and medium-speed/low-friction roads. Simulation results show that compared with the uncontrolled case and the variable steering ratio control strategy alone, the proposed control strategy effectively improves the vehicle dynamic response and stability. Under the high-speed/high-friction condition, the lateral displacement error is reduced from 6.37% to 3.57%; under the medium-speed/low-friction condition, it is reduced from 9.74% to 2.11%. This study enhances the stability and active safety of SBW vehicles and provides valuable insights for the development of advanced SBW systems.

, authors=Yingwei Yang, Limin Niu, Menghan Wang, Zeyun Wen, Jingjie Cao, authorsList=Yingwei Yang, Limin Niu, Menghan Wang, Zeyun Wen, Jingjie Cao, authorCompany=null, correspAuthors=Limin Niu, 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=1319244970029073354, articleId=1319244969513173960, tenantId=1146029695717560320, journalId=1189621681917173762, language=CN, title=线控转向汽车主动转向稳定性的自适应控制研究, columnId=1319244967223078978, journalTitle=汽车技术, columnName=线控转向车辆横向稳定性与运动跟踪控制技术专题, runingTitle=null, highlight=null, articleAbstract=

针对提升线控转向（SBW）车辆的操纵稳定性和主动安全性，提出一种基于滑模控制的线控转向稳定性控制策略，该策略将横摆角速度与质心侧偏角共同作为反馈变量。通过粒子群-灰狼优化（PSO-GWO）算法优化横摆角速度定增益的变传动比，满足线控转向车辆低速灵敏和高速稳定特征；以改进型滑模控制为基础，设计自适应全局快速终端滑模控制器以减弱系统抖振，由滑模控制器产生的附加前轮转角改善车辆操纵稳定性。利用MATLAB/Simulink搭建线控转向系统模型，联合CarSim仿真，分别在高速高附着系数及中速低附着系数路面的双移线工况下进行仿真分析。结果表明：相较于无控制和单一变传动比控制策略，提出的控制策略在高速高附着系数工况下，横向位移误差由6.37%降低至3.57%；在中速低附着系数工况下，横向位移误差由9.74%降低至2.11%，能够有效改善车辆动态响应与稳定性。

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