Estimation of Wheel Center Forces of a Car, Without Neither Load Sensor Nor Strain Gauge Measurements When Crossing a Groove on the Road

To design a vehicle suspension the knowledge of wheel loads is required. These loads are due to road unevenness and can be identified thanks the acquisition of measurements during vehicle rolling on roads or tracks. Some offline methods are used to identify them; most of these methods are based on transfer functions between points of measurements and consider the hypothesis of linear dynamic behavior of the vehicle. This hypothesis leads to misestimation of the exceptional load. We propose an approach based on a nonlinear multi-body model of the half-vehicle and an extended Kalman filter augmented and constrained for the data fusion with measurements from accelerometers, gyrometer, tachometer, and GPS. This half vehicle model lies in a 2D plane. The Kalman state vector is composed of positions and velocities of each solid, the road/track loads are unknown but estimated by the filter, and the state prediction is constrained by kinematic links between bodies.