On-line estimation of a stability metric including grip conditions and slope: Application to rollover prevention for all-terrain vehicles
| Autor: | Christophe Debain, Mathieu Richier, Benoit Thuilot, Roland Lenain |
|---|---|
| Přispěvatelé: | Technologies et systèmes d'information pour les agrosystèmes (UR TSCF), Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Laboratoire des sciences et matériaux pour l'électronique et d'automatique (LASMEA), Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-Centre National de la Recherche Scientifique (CNRS), Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
050210 logistics & transportation
0209 industrial biotechnology Engineering VEHICULE TOUT TERRAIN Observer (quantum physics) Stability criterion business.industry Rolling resistance 05 social sciences Stability (learning theory) 02 engineering and technology Kalman filter Rollover Acceleration 020901 industrial engineering & automation Control theory Backstepping 0502 economics and business [SDE]Environmental Sciences STABILITE DE VEHICULE RENVERSEMENT DE VEHICULE business CONDUITE DE VEHICULE |
| Zdroj: | IROS'11, IEEE/RSJ International conference on intelligent robots and systems IROS'11, IEEE/RSJ International conference on intelligent robots and systems, Sep 2011, San Francisco, United States. p.-p IROS |
| Popis: | [Departement_IRSTEA]Ecotechnologies [TR1_IRSTEA]INSPIRE; International audience; Rollover is the principal cause of serious accidents for All-Terrain Vehicles (ATV), especially for light vehicles (e.g.quad bikes). In order to reduce this risk, the development of active devices, contributes a promising solution. With this aim, this paper proposes an algorithm allowing to predict the rollover risk, by means of an on-line estimation of a stability criterion. Among several rollover indicators, the Lateral Load Transfer (LLT) has been chosen because its estimation needs only low cost sensing equipment compared to the price of a light ATV. An adapted backstepping observer associated to a bicycle model is first developed, allowing the estimation of the grip conditions. In addition, the lateral slope is estimated thanks to a classical Kalman filter relying on measured acceleration and roll rate. Then, an expression of the LLT is derived from a roll model taking into account the grip conditions and the slope. Finally, the LLT value is anticipated by means of a prediction algorithm. The capabilities of this system are investigated thanks to full scale experiments with a quad bike. |
| Databáze: | OpenAIRE |
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