Sideslip Angle Estimation of an Electric Ground Vehicle via Finite-Frequency $\mathcal {H}_{\infty}$ Approach

Abstract

The lateral stability is critically important especially when the vehicle is steered at a high longitudinal speed. Loss of lateral stability would lead to severe accidents. Therefore, the study of lateral stability has been a hot topic for decades. In order to monitor the lateral stability or improve the stability by using the feedback control, the sideslip angle is an important index. However, the sideslip angle is not measurable by using an affordable physical sensor. An alternative approach is to estimate the sideslip angle with the measurements of relatively cheap sensors. In this paper, we investigate the problem of sideslip angle observer design for an electric ground vehicle (EGV). The EGV is equipped with an advanced navigation system. The lateral velocity, the longitudinal velocity, and the yaw rate are available. Thus, the sideslip angle which is defined as the ratio of lateral velocity and longitudinal velocity is also available. Meanwhile, the hand-wheel steering angle is also measurable in this application. The main work is to estimate the sideslip angle with the measurements of yaw rate based on the vehicle lateral dynamics. The dynamic model is first established and the parameters are identified with experimental data. Since the dynamic model is nonlinear, in order to facilitate the system analysis and observer design, the nonlinear model is transformed to a linear-parameter-varying (LPV) system. An observer is proposed based on the LPV form. By defining the estimation error, a compact system which contains the estimation error and the original dynamics is obtained. Considering the frequency of the front-wheel steering angle, the finite-frequency $\mathcal {H}_{\infty}$ performance of the compact system is exploited. An optimal observer design method is then developed. For the EGV, the observer is designed according to the developed method. The performance of the designed observer is illustrated with experimental test data.