Integrated model predictive control and velocity estimation of electric vehicles

Abstract

In this paper, an integrated estimation and control system is developed for the stability and traction control of electric vehicles. A model predictive control technique is used to track the desired vehicle yaw rate while maintaining small lateral velocity and tire slip ratios. This paper proposes a new method to control the lateral stability of the vehicle. In this method, the lateral vehicle velocity is controlled indirectly by adjusting the reference yaw rate. This reduces the size of the prediction model and its computational complexity. The controller requires the vehicle’s lateral and longitudinal velocities as well as its tire forces for stability and traction control. This paper also proposes a novel velocity estimation scheme that uses the combined vehicle kinematics and tire model. The developed Kalman-based estimator provides velocities and lateral forces at each corner that are robust to changes in the road condition. The combined model-based and kinematic-based estimation structure mitigates some common problems of the widely used kinematic-based estimators such as the spikes and drifting issues. The stability of the proposed time-varying estimator is also investigated. The designed control and estimation scheme are experimentally validated on various driveline configurations and proven to provide reliable results.