Autonomous emergency braking (AEB) is an active safety technology which aims to prevent collisions by operating harsh braking. When AEB is activated on split-μ roads, the yaw moment generated by the asymmetric braking forces will lead to losing control of the vehicle. In this study, a coordinated control scheme of steer-by-wire (SBW) and brake-by-wire (BBW) is developed to solve this problem. An anti-lock braking system is achieved by a sliding mode controller. Besides, two model predictive controllers based on a 7-degree-of-freedom vehicle dynamics model are proposed for different road adhesion conditions. According to the simulation results, the proposed scheme can maintain the stability of the vehicle and achieve a satisfying braking efficiency under various friction differences between the two-side wheels. At last, the experiments are also carried out to verify the effectiveness and the real-time performance of the proposed scheme on a hardware-in-loop bench of BBW and SBW.
The traction control system (TCS) allows for better power performance and stability of the vehicle. On-demand four-wheel-drive (OD4WD) vehicles are expected to start up in complex situations such as only one wheel landing on the high friction road surface. Therefore, the TCS applied in OD4WD vehicles requires coordinated control of the engine, brake, and transfer case. If the controller is not well designed, the performance of the vehicle would decrease and the components may be damaged. Aiming to deal with the traction control problem of OD4WD vehicles, a coordinated controller is proposed in this paper. First, the models of the main components of the OD4WD vehicle are analyzed. Then, the coordinated controller is designed based on the active disturbance rejection controller (ADRC), the fuzzy controller, and the sliding-mode controller. The estimation and calculation methods of the necessary information are also designed. After that, vehicle experiments of the start-up process are carried out in typical situations to validate the effectiveness of the controller. Results show that the coordinated controller ensures power performance and improves the stability of the vehicle.
This paper addresses the crucial issues of autonomous ground vehicles (AGVs), that is, smooth and accurate path following, especially when input constraints and external disturbances exist. A nonlinear H∞ control scheme is proposed based on the neural network (NN) and policy iteration (PI) algorithm. Firstly, a nonlinear system model for path following of AGVs is constructed, which takes vehicular nonlinear cornering behavior into account. Then, a nonlinear H∞ controller is designed based on the Hamilton-Jacobi-Isaacs (HJI) equation. Wherein, the established NN is leveraged to approximate the HJI equation’s performance function, and the PI algorithm is developed to learn the solution to the HJI equation. Finally, the convergence and closed-loop stability of the proposed strategy are demonstrated. Simulation results show that the proposed controller can significantly improve the response speed, driving smoothness and accuracy of path following in high-speed driving condition with strong robustness against external disturbances.
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