In any automotive system, the tires play a very crucial role in defining both the safety and performance of the vehicle. The interaction between the tire and the road surface determines the vehicle's ability to accelerate, decelerate and steer. Having information about this interaction in real-time can be very valuable for the on-board advanced active safety systems to mitigate the risks ahead of time and keep the vehicle stable. The crucial information which can be obtained from the tire includes but are not limited to tire-road friction, tire forces (longitudinal, lateral), normal load, road surface characteristics and tire pressure. This information can be acquired through indirect vehicle dynamics based estimation algorithms or through direct measurements using sensors inside the tire. However, the indirect estimations fail to give an accurate measure of the vehicle state in certain conditions (e.g. side winds, road banking, surface change) and require ABS or VSC activation before the estimation begins. Therefore, to improve the performance of these active stability systems, direct measurement based approaches must be explored. This research expands the applications of Intelligent tire and focuses on using the sensor based measurement approach to develop estimation algorithms relating to tire force measurement. A tri-axial accelerometer is attached to the inner liner of the tire (Intelligent Tire) and two of such tires are placed on an instrumented (MSW, VBox, IMU, Encoders) VW Jetta. Different controlled tests are carried out on the instrumented vehicle and the Intelligent tire signal is analyzed to extract features related to the tire forces and pressure. Due to unavailability of direct force measurements at the wheel, a VW Jetta simulation model is developed in CarSim and the extracted features are validated with a good correlation. / Master of Science

Ces dernières décennies, la recherche et l'application de l'automatique dans les domaines de l'automobile, a contribué fortement dans les aspects sécurité, confort des usagers, économie d'énergie et aide au pilotage.Dans ce contexte, l'objectif principal de cette thèse est le développement d'observateurs par modes de glissement pour l'estimation des états dynamiques, les paramètres dynamiques ainsi que les attributs de la route (dévers de la route), considérés comme des entrées inconnues. Ce type d'observateur est basé sur la théorie des systèmes à structures variables et par l'utilisation d'un modèle représentant de façon réaliste le comportement dynamique du véhicule. A cet effet une proposition de découpage de modèle dynamique complet du véhicule en trois sous-systèmes basé sur le théorie de la passivité a été proposé. Toutes les approches développées ont été validées sur les deux simulateurs de véhicules SCANeRstudio et SIMK106N. / The general framework of the research is the application of the nonlinear control tools (Robust control, Sliding mode Observer, Algebric approach,...) in order to improve the security of vehicle. The estimation of tire road force has become an intensive research area as the interest in information technology in vehicles grows. More and more new safety technologies and approaches are introduced in the automotive environment. Therefore, the problem of traction control for ground vehicles is of enormous importance to automotive industry.We split the dynamic model of vehicle into five subsystems regrouped in three blocks and then show and justify the rationale behind the successful splitting. Thesubsystems and the overall system obey to the passivity property. Robust observer are proposed to estimate the road features.

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