Abstract:

In order to improve the active safety of four-wheel independent drive electric vehicles under extreme conditions such as low adhesion road driving and high-speed steering， a predictive control-based dynamic integrated control method is proposed in this paper. Firstly， in order to balance the modeling accuracy of the prediction model and the computational burden of the controller， the nonlinear yaw dynamic model is simplified by a piecewise affine approximation， and then the prediction model of the hybrid system is established. Secondly， the instability mechanism of the multi-time-varying parameter system is analyzed. The maneuvers with bifurcation are defined as the extreme conditions， and the unified vehicle stability judgement method for different extreme conditions such as low adhesion and high speed is developed to determine the switching mechanism of the control mode. Then， the integrated dynamic control strategy based on the robust hybrid predictive control algorithm is proposed， which systematically considers the vehicle speed variation and tire nonlinear lateral deflection characteristics under the extreme conditions， and coordinately optimizes the anti-skid performance， yaw stability and other safety indexes. The processor-in-the-loop test shows that the proposed integrated dynamic control strategy can meet the control requirements of low adhesion road driving and high-speed steering conditions， and significantly improve the active safety of the vehicle under extreme conditions.

Key words: four-wheel independent drive electric vehicles, extreme maneuver, veicle dynamic control, model predictive control