{"title":"Multi-actuated ground vehicle tyre force estimation through a coupled 1D simulation-estimation framework","authors":"Marco Viehweger, S. V. Aalst, F. Naets, W. Desmet","doi":"10.1109/ICCVE45908.2019.8965229","DOIUrl":null,"url":null,"abstract":"This paper disseminates the use of a coupled 1D simulation-estimation framework employed for multi-actuated ground vehicle tyre force virtual sensing. The forces generated in the tyre contact patches govern the vehicle motion and behaviour on the road. Therefore, they are highly relevant for Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) technologies, especially when it comes to ensuring vehicle stability and driving safety in extreme manoeuvres. However, some ADAS and AD features require accurate and robust estimation of additional vehicle dynamics related quantities. Thus, this paper proposes a framework for the consistent use of 1D vehicle models of different complexity together with state-of-the-art estimation techniques to enable joint state, disturbance, parameter (SDP) estimation.","PeriodicalId":384049,"journal":{"name":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Conference on Connected Vehicles and Expo (ICCVE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCVE45908.2019.8965229","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This paper disseminates the use of a coupled 1D simulation-estimation framework employed for multi-actuated ground vehicle tyre force virtual sensing. The forces generated in the tyre contact patches govern the vehicle motion and behaviour on the road. Therefore, they are highly relevant for Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) technologies, especially when it comes to ensuring vehicle stability and driving safety in extreme manoeuvres. However, some ADAS and AD features require accurate and robust estimation of additional vehicle dynamics related quantities. Thus, this paper proposes a framework for the consistent use of 1D vehicle models of different complexity together with state-of-the-art estimation techniques to enable joint state, disturbance, parameter (SDP) estimation.