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Path-dependent rollover prevention for critical truck maneuvers
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Vehicular Systems. Linköping University, Faculty of Science & Engineering.
2016 (English)In: The Dynamics of Vehicles on Roads and Tracks: Proceedings of the 24th Symposium of the International Association for Vehicle System Dynamics (IAVSD 2015), Graz, Austria, 17-21 August 2015 / [ed] Martin Rosenberger, Manfred Plöchl, Klaus Six, Johannes Edelmann, CRC Press, 2016, 317-326 p.Conference paper (Refereed)
Abstract [en]

Predicting rollover is usually performed using rollover indices, where rollover is anticipated when the indices reach certain threshold values. If knowledge about the vehicle driving path is available, rollover can be detected and prevented earlier. In this work, the rollover-prediction and rollover-prevention abilities for simple vehicle models are evaluated and compared against a high-fidelity vehicle model. The analysis is performed by using the models in critical and rolloverprone maneuvers, generated with optimal control methods. The main conclusion is that a simple point-mass model would be sufficient in a velocity based rollover-prevention controller.

Place, publisher, year, edition, pages
CRC Press, 2016. 317-326 p.
National Category
Vehicle Engineering
Identifiers
URN: urn:nbn:se:liu:diva-132696DOI: 10.1201/b21185-36ISI: 000385792300034ISBN: 9781138028852 (print)ISBN: 9781498777025 (eBook)OAI: oai:DiVA.org:liu-132696DiVA: diva2:1048100
Conference
24th Symposium of the International Association for Vehicle System Dynamics (IAVSD), Graz, Austria, August 17-21, 2015
Available from: 2016-11-20 Created: 2016-11-18 Last updated: 2016-11-25Bibliographically approved

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