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This paper presents a strong robust path tracking control method which is based on sliding mode control and active disturbance rejection control. Firstly, by constructing a desired yaw angle function, which can guarantee that the deviations of the vehicle actual lateral displacement from the desired path converges to zero when the yaw angle of the vehicle approaches the desired yaw angle, so that the complex path tracking control problem can be transformed into easy to implement yaw angle tracking control problem. Then, a robust vehicle yaw angle tracking controller is constructed. The controller consists of two parts: the extended state observer and the nonlinear error feedback control law. The extended state observer is used to estimate the unmodeled dynamics and unknown external perturbations of the system in real time.

In this paper, the variable steering ratio control strategies under normal driving conditions and emergency driving conditions were proposed. The variable steering ratio control under normal driving conditions is based on variable yaw rate gain, and takes into account the driver’s operating habits and vehicle handling stability. The steering ratio varies with the vehicle speed and the steering wheel angle, which ensures the vehicle steering sensitivity at low speed and the steering stability at high speed. The variable steering ratio control under the emergency driving conditions is based on yaw rate dynamic feedback control, and the steering ratio varies with the vehicle movement status. We use active steering control which is based on active disturbance rejection control to achieve yaw rate dynamic feedback control, which can improve vehicle stability without affecting the longitudinal movement of vehicle.

With the load of urban traffic system becomes more serious, the Automatic Parking System (APS) plays an important role in alleviating the burden of drivers and improving vehicle safety. The APS is consisted of environmental perception, path planning and path following. The path following controls the lateral movement of vehicle during the parking process, and requires the trajectory tracking error to be as small as possible. At present, some control algorithms are used including PID control, pure pursuit control, etc. However, these algorithms relying heavily on parameters and environment, have some problems such as slow response and low precision. To solve this problem, a path following control method based on Model Predictive Control (MPC) algorithm is proposed in this paper. Firstly, Kinematic vehicle model and path tracker based on MPC algorithm are built. Secondly, a test bench that composed of CANoe hardware in the loop (HIL) system and steering wheel system is built.

With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.

This paper studies the drivability of Hybrid Electric Vehicles (HEV), and presents some methods to improve the drivability based on experiment results. First, the working principle of HEV is introduced and the hybrid powertrain is modeled. The jerk of vehicle is applied in this paper to evaluate the drivability of HEV. After studying the cause of jerk, a series of experiments of vehicle starting, state-changing, shifting and braking are designed and implemented on a parallel HEV with an automated mechanical transmission. Analysis of these experiment results shows that optimization of clutch control and cooperation of the engine and the motor on speed and torque are effective in reducing the jerk of vehicle.