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It is very significant for autonomous vehicles to have the ability to operate beyond the stable handling limits, which plays a vital role in vehicles’ active safety and enhances riding and driving pleasure. For traditional vehicles, it is rather difficult to control the longitudinal speed, sideslip angle and yaw rate simultaneously when drifting along a given trajectory because they are under-actuated. Nevertheless, for a 4-wheel-independent-drive (4WID) vehicle, it is possible and controllable thanks to its over-actuated characteristics. This article designs a trajectory following control strategy for automated drifting of 4WID vehicles. First, a double-track 7 degree of freedom (7DOF) vehicle dynamic model is established, which incorporates longitudinal and lateral load transfer and considers nonlinear tire models. The controller which proposes a hierarchical architecture is then designed.

In contrast to a normal vehicle, a 4-wheel steer (4WS) and 4-wheel independent drive (4WID) vehicle provides more flexibilities in vehicle dynamic control and better handling performance, since both the steer angle and drive torque of each wheel can be controlled. However, for motorsports, how much lap time can be improved with such a vehicle is a problem few discussed. So, this paper focuses on the racing line optimization and lap time improvement for a 4WS &4WID vehicle. First, we optimize the racing line and lap time of three given circuits with the genetic algorithm (GA) and interior-point method, and several objective functions are compared. Next, to evaluate the lap time improvement of 4WS & 4WID, a detailed vehicle dynamic model of our 4WS & 4WID platform vehicle is built in Carsim. To follow the racing line, a path following controller which contains a PID speed controller and a model predictive control (MPC) yaw rate controller is built.

To further explore the potential of fuel economy for hybrid electric vehicle (HEV), a methodology of demand power optimization is proposed. The fuel consumption depends not only on the EMS, but also on the way to operate vehicle. A control strategy to adjust driver’s demand before power splitting is necessary. To get accurate and reliable control strategy, two aspects are the most important. First, a rigorous and organized modeling approach is a base to describe complicated powertrain system of HEV. The energetic macroscopic representation (EMR) is a graphical synthetic description of electromechanical conversion system based on energy flow. A powertrain architecture of HEV is described explicitly via the EMR. Second, the effectiveness of EMS and the reasonability of driving operations are vital.

Lane changing is an essential action in commercial vehicles to prevent collisions. However, steering system malfunctions significantly escalate the risk of head-on collisions. With the advancement of intelligent chassis control technologies, some autonomous commercial vehicles are now equipped with a four-wheel independent braking system. This article develops a lane-changing control strategy during steering failures using torque vectoring through brake allocation. The boundaries of lane-changing capabilities under different speeds via brake allocation are also investigated, offering valuable insights for driving safety during emergency evasions when the steering system fails. Firstly, a dual-track vehicle dynamics model is established, considering the non-linearity of the tires. A quintic polynomial approach is employed for lane-changing trajectory planning. Secondly, a hierarchical controller is designed.