How to reasonably coordinate and control the torque of four wheels to enhance vehicle performance is an important research problem of the four in-wheel-motor independent-drive electric vehicle (4MIDEV). In this paper, a coordinated hierarchical control strategy for the dynamic wheel torque of 4MIDEV steering is proposed, which considers both safety and energy-saving performance. The innovation of this paper lies in two new valuable algorithms in the top and bottom level controller, respectively. Besides the optimal control method on the basis of the 2-degree of freedom (DoF) ideal model in the top level controller, a novel model predictive control method based on the 7-DoF dynamic model is put forward to obtain two virtual generalized forces required during vehicle driving. In the bottom level controller, a novel optimal allocation (OA) algorithm is brought forward to improve the safety and energy-saving performance. The tire stability margin and the electric power of driving system balancing the driving energy consumption and regenerative braking energy recovery are considered in the quadratic objective function of OA algorithm at the same time. Carsim-Simulink joint simulation results under open-loop and closed-loop steering conditions illustrate that, compared with the 2-DoF LQR control method, the 7-DoF MPC method could effectively improve vehicle handling stability and safety. The bottom optimal allocation algorithm can not only improve the vehicle handling stability, but also make the driving system more energy-saving.

Mode transition control problem in a hybrid powertrain has always been a central concern, because many complicated transient dynamics are involved in this process, such as engine-start, clutch engagement, and actuator control, etc. Especially for a parallel hybrid electric vehicle (HEV), the drivability problem during mode transition process is significant yet challenging to solve. In this paper, a new efficient mode transition control method with adaptive dual-loop control framework is proposed for the clutch engagement in a parallel HEV. Firstly, the expected clutch engaging speed can be calculated by compromising the transient vehicle jerk and the clutch slipping power. Utilizing the integral transformation, the demand clutch position trajectory for the inner loop can be obtained. Considering the uncertainties and the backlash in the clutch actuator system, an adaptive state feedback controller is designed in the inner loop. Simulation and experimental results show that the proposed control method can effectively improve the HEV drivability while taking clutch actuator uncertainties into consideration. Furthermore, compared with the control method commonly used in practice, the time of mode transition process can be shortened and vehicle jerk can be controlled within an acceptable range using the proposed method.