  Robust estimation of vehicle sideslip angle is essential for stability
control applications. However, the direct measurement of sideslip angle is
expensive for production vehicles. This paper presents a novel sideslip
estimation algorithm which relies only on sensors available on passenger and
commercial vehicles. The proposed method uses both kinematics and dynamics
vehicle models to construct extended Kalman filter observers. The estimate
relies on the results provided from the dynamics model observer where the tire
cornering stiffness parameters are updated using the information provided from
the kinematics model observer. The stability property of the proposed algorithm
is discussed and proven. Finally, multiple experimental tests are conducted to
verify its performance in practice. The results show that the proposed approach
provides smooth and accurate sideslip angle estimation. In addition, our novel
algorithm provides reliable estimates of bank angles and lateral acceleration
sensor bias.
