Automotive Steering System and Its Controller Design for Intelligent Vehicles

Abstract

With the rapid development of intelligent vehicles technology, it is extremely urgent to solve environmental pollution and energy crisis. The electric intelligent vehicles technology can accelerate the world to move towards low carbonization and intelligence. In this article, one automatic steering system and its controller are designed with this electric vehicle as the verification platform. First, based on the digital mock-up (DMU) module of the CATIA digital prototype, the motion simulation of the automatic steering system is carried out. Then, the transient dynamics and fatigue analysis module from ANSYS Workbench 16.0 software is used to simulate and analyze the transmission mechanism. After verifying the reasonable strength of the real vehicle parts, the original platform steering system is reformed. Our intelligent vehicle uses a monocular charge-coupled device (CCD) to detect road marking lines and then employs a linear two degrees of freedom (2-DOF) vehicle model to establish a preview deviation model based on the visual navigation lane lines. A vehicle lateral control method combining fuzzy logic rules, adaptive proportional-integral-derivative (PID) control strategy, and preview deviation is designed. A lateral controller is built using Simulink software for lane tracking simulation, and a good tracking effect is obtained. Finally, the results of low-speed real vehicle tests show that the vehicle can stably track the target lane line at low-speed conditions.