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Although tire forces are important as factors governing the behavior of a vehicle, current chassis control systems have used tire forces indirectly estimated. Hence, this research developed Intelligent Tire System (i-Tire) that can measure tire forces directly. This system used a deform gage and a surface acoustic wave (SAW) sensor, which are capable of passive radio communication. The performance of this developed system was tested with a tire test system (MTS Flat Trac) and a vehicle test.

Rollover is one of the significant life threatening factors in SUVs (Sports Utility Vehicles). By applying braking or steering, active roll stability controllers help prevent rollover accidents in SUVs. The performance of these controllers is very sensitive to vehicle inertial parameters such as vehicle mass and mass center height. In this paper, a unified estimation method for vehicle mass is proposed considering available driving conditions, where three estimation algorithms are developed based on longitudinal, lateral or vertical vehicle dynamics, respectively. The first algorithm is designed using the longitudinal vehicle dynamics and the recursive least square with the disturbance observer technique for longitudinal traveling case. The second algorithm is designed using the lateral vehicle dynamics where the lateral velocity is estimated with the kinematic vehicle model via the Kalman filter.