Jongyong Do , Dongyoon Hyun , Kyoungseok Han , Seibum B. Choi
{"title":"考虑轮胎动态特性的轮胎纵向刚度实时估算","authors":"Jongyong Do , Dongyoon Hyun , Kyoungseok Han , Seibum B. Choi","doi":"10.1016/j.mechatronics.2023.103120","DOIUrl":null,"url":null,"abstract":"<div><p><span>To enhance the effectiveness of active safety control, the tire–road friction coefficient (TRFC) must be precisely estimated, and the longitudinal tire stiffness coefficient is an important vehicle dynamic parameter to estimate TRFC. In this research, we present an observer that improves the performance of longitudinal tire stiffness coefficient estimation by applying tire dynamics that were previously applied in the </span>lateral direction<span> to the longitudinal direction<span>. To begin, we model longitudinal tire dynamics using the relaxation length concept and validate the model using vehicle braking tests. We develop an observer that estimates the longitudinal tire stiffness coefficient by integrating the proposed tire dynamics and vehicle dynamics. The observer, which is based on an extended Kalman filter<span>, can be applied to nonlinear systems and successfully removes noise from wheel speed measurement. The observer’s estimation performance is verified using CarSim simulation and vehicle tests, and the results are compared to existing approaches that do not account for longitudinal tire dynamics. Even in the transient section when the vehicle begins accelerating, the difference between the estimate and the reference value is about 0.3% using the proposed method, but if tire dynamics are not taken into account, the estimate is 6.5% lower than the reference value.</span></span></span></p></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"98 ","pages":"Article 103120"},"PeriodicalIF":3.1000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Real-time estimation of longitudinal tire stiffness considering dynamic characteristics of tire\",\"authors\":\"Jongyong Do , Dongyoon Hyun , Kyoungseok Han , Seibum B. Choi\",\"doi\":\"10.1016/j.mechatronics.2023.103120\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><span>To enhance the effectiveness of active safety control, the tire–road friction coefficient (TRFC) must be precisely estimated, and the longitudinal tire stiffness coefficient is an important vehicle dynamic parameter to estimate TRFC. In this research, we present an observer that improves the performance of longitudinal tire stiffness coefficient estimation by applying tire dynamics that were previously applied in the </span>lateral direction<span> to the longitudinal direction<span>. To begin, we model longitudinal tire dynamics using the relaxation length concept and validate the model using vehicle braking tests. We develop an observer that estimates the longitudinal tire stiffness coefficient by integrating the proposed tire dynamics and vehicle dynamics. The observer, which is based on an extended Kalman filter<span>, can be applied to nonlinear systems and successfully removes noise from wheel speed measurement. The observer’s estimation performance is verified using CarSim simulation and vehicle tests, and the results are compared to existing approaches that do not account for longitudinal tire dynamics. Even in the transient section when the vehicle begins accelerating, the difference between the estimate and the reference value is about 0.3% using the proposed method, but if tire dynamics are not taken into account, the estimate is 6.5% lower than the reference value.</span></span></span></p></div>\",\"PeriodicalId\":49842,\"journal\":{\"name\":\"Mechatronics\",\"volume\":\"98 \",\"pages\":\"Article 103120\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2023-12-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mechatronics\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0957415823001769\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"AUTOMATION & CONTROL SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mechatronics","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0957415823001769","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"AUTOMATION & CONTROL SYSTEMS","Score":null,"Total":0}
Real-time estimation of longitudinal tire stiffness considering dynamic characteristics of tire
To enhance the effectiveness of active safety control, the tire–road friction coefficient (TRFC) must be precisely estimated, and the longitudinal tire stiffness coefficient is an important vehicle dynamic parameter to estimate TRFC. In this research, we present an observer that improves the performance of longitudinal tire stiffness coefficient estimation by applying tire dynamics that were previously applied in the lateral direction to the longitudinal direction. To begin, we model longitudinal tire dynamics using the relaxation length concept and validate the model using vehicle braking tests. We develop an observer that estimates the longitudinal tire stiffness coefficient by integrating the proposed tire dynamics and vehicle dynamics. The observer, which is based on an extended Kalman filter, can be applied to nonlinear systems and successfully removes noise from wheel speed measurement. The observer’s estimation performance is verified using CarSim simulation and vehicle tests, and the results are compared to existing approaches that do not account for longitudinal tire dynamics. Even in the transient section when the vehicle begins accelerating, the difference between the estimate and the reference value is about 0.3% using the proposed method, but if tire dynamics are not taken into account, the estimate is 6.5% lower than the reference value.
期刊介绍:
Mechatronics is the synergistic combination of precision mechanical engineering, electronic control and systems thinking in the design of products and manufacturing processes. It relates to the design of systems, devices and products aimed at achieving an optimal balance between basic mechanical structure and its overall control. The purpose of this journal is to provide rapid publication of topical papers featuring practical developments in mechatronics. It will cover a wide range of application areas including consumer product design, instrumentation, manufacturing methods, computer integration and process and device control, and will attract a readership from across the industrial and academic research spectrum. Particular importance will be attached to aspects of innovation in mechatronics design philosophy which illustrate the benefits obtainable by an a priori integration of functionality with embedded microprocessor control. A major item will be the design of machines, devices and systems possessing a degree of computer based intelligence. The journal seeks to publish research progress in this field with an emphasis on the applied rather than the theoretical. It will also serve the dual role of bringing greater recognition to this important area of engineering.