Zhihong Man;Mingcong Deng;Zenghui Wang;Qing-Long Han
{"title":"A New Parameter Estimation Methodology Using Steady State Yaw Rate Measurements for Lateral Vehicle Dynamics","authors":"Zhihong Man;Mingcong Deng;Zenghui Wang;Qing-Long Han","doi":"10.1109/JAS.2025.125366","DOIUrl":null,"url":null,"abstract":"In this paper, the lateral dynamics of road vehicles (LDRV) is further studied from the viewpoint of vehicle informatics. It is seen that LDRV is first decoupled and the vehicle slip angle is proved to be observable from the yaw rate measurements. A new methodology of parameter estimation using steady-state yaw rate measurements (PESYRM) is then developed to accurately estimate the parameters of LDRV. The important characteristics of PESYRM comprise four parts: 1) The steering angle input to LDRV is chosen as the linear combination of sinusoids; 2) Only the steady state information of yaw rate in any fundamental period is required to accurately estimate the unknown parameters of LDRV; 3) Unlike many existing parameter estimation methods, the time consuming computing of the inverse of high-dimensional data matrix is avoided by making full use of the orthogonal properties of trigonometric base functions; 4) All of system information of LDRV is embedded in the measurements of the steady state yaw rate in any fundamental period. A simulation example is carried out to show the advantages and effectiveness of the new research findings for LDRV.","PeriodicalId":54230,"journal":{"name":"Ieee-Caa Journal of Automatica Sinica","volume":"13 9","pages":"2003-2018"},"PeriodicalIF":18.3000,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ieee-Caa Journal of Automatica Sinica","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11716137/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/10/1 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the lateral dynamics of road vehicles (LDRV) is further studied from the viewpoint of vehicle informatics. It is seen that LDRV is first decoupled and the vehicle slip angle is proved to be observable from the yaw rate measurements. A new methodology of parameter estimation using steady-state yaw rate measurements (PESYRM) is then developed to accurately estimate the parameters of LDRV. The important characteristics of PESYRM comprise four parts: 1) The steering angle input to LDRV is chosen as the linear combination of sinusoids; 2) Only the steady state information of yaw rate in any fundamental period is required to accurately estimate the unknown parameters of LDRV; 3) Unlike many existing parameter estimation methods, the time consuming computing of the inverse of high-dimensional data matrix is avoided by making full use of the orthogonal properties of trigonometric base functions; 4) All of system information of LDRV is embedded in the measurements of the steady state yaw rate in any fundamental period. A simulation example is carried out to show the advantages and effectiveness of the new research findings for LDRV.
期刊介绍:
The IEEE/CAA Journal of Automatica Sinica is a reputable journal that publishes high-quality papers in English on original theoretical/experimental research and development in the field of automation. The journal covers a wide range of topics including automatic control, artificial intelligence and intelligent control, systems theory and engineering, pattern recognition and intelligent systems, automation engineering and applications, information processing and information systems, network-based automation, robotics, sensing and measurement, and navigation, guidance, and control.
Additionally, the journal is abstracted/indexed in several prominent databases including SCIE (Science Citation Index Expanded), EI (Engineering Index), Inspec, Scopus, SCImago, DBLP, CNKI (China National Knowledge Infrastructure), CSCD (Chinese Science Citation Database), and IEEE Xplore.