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This paper presents an Interacting Multiple Model (IMM) based side slip angle estimation method to estimate side slip angle under various road conditions for vehicle stability control. Knowledge of the side slip angle is essential enhancing vehicle handling and stability. For the estimation of the side slip angles in previous researches, prior knowledge of tire parameters and road conditions have been employed, and sometimes additional sensors have been needed. These prior knowledge and additional sensors, however, necessitates many efforts and make an application of the estimation algorithm difficult. In this paper, side slip angle has been estimated using on-board vehicle sensors such as yaw rate and lateral acceleration sensors. The proposed estimation algorithm integrates the estimates from multiple Kalman filters based on the multiple models with different parameter set.

The growing concern surrounding Sports Utility Vehicle (SUV) rollover incidences and their consequences have prompted to investigate the sensitivity of critical vehicle parameters on rollover. In this paper, dynamic rollover simulation of Sports Utility Vehicles is carried out using a validated nonlinear vehicle model in Matlab/Simulink. A standard model is considered and critical vehicle parameters like CG height, track width and wheel base are varied within chosen specified limits to study its influence on roll behavior during Fishhook steering maneuver. A roll stability criterion based on two wheel lift off phenomenon is adopted for rollover propensity prediction. Further dynamic rollover characteristics of the vehicle are correlated with Static Stability Factor (SSF), Roll Stability Factor (RSF) and Two Wheel Lift off Velocity (TWLV).