Study of the estimation of vehicle sideslip angle based on CDKF

The estimation of vehicle dynamic plays an important role in the vehicle stability control system. Conventional methods such as extend Kalman filter (EKF) have the disadvantage of low accuracy. Therefore, it is essential to adopt a proper estimation method for the key vehicle status parameters. Central difference Kalman filter (CDKF) is a new nonlinear filtering method, which adopts the interpolation formulas for the state estimation on approximation of nonlinear systems and reduces the affection of the linearization of system accuracy. CDKF method is conducted to estimate the vehicle sideslip angle based on measurable variables. The simulation results show that the estimation of vehicle sideslip angle based on CDKF has a better consistency with the reference value.