Abstract:

The model predictive control (MPC) algorithm was used to establish the predictive control model of vehicle lateral stability to estimate the electric vehicle state accurately and improve the safety performance of vehicle, based on two degrees of freedom model. The vehicle sideslip angle, yaw angular and tire slip ratio were selected as state variables and the four-wheel torque distribution was treated as control variables. Considering the driver's operation load and the smooth of steering and driving/braking operations, the cost function of model was built. The extended Kalman filtering (EKF) estimator was designed to estimate and evaluate the current state of the vehicle. And the rolling horizon optimization was solved using Quadratic Program (QP) algorithm to obtain the optimal torque of the four wheels. The co-simulation platform of Simulink and Carsim was constructed and simulated under the high and low attached road surface respectively on the premise that the steering wheel was sinusoidal input. The results show that the MPC medel can effectively maintain the vehicle's lateral stability.

Key words: electric vehicle, lateral stability control, co-simulation , model predictive control (MPC), extended Kalman filtering (EKF)