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Zeng Li,Gaojian Cui,Shaosong Li,Niaona Zhang,Yunsheng Tian,Xiaoqiang Shang 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.4
To address the failure to consider vehicle states in region of interest (ROI) prediction, we propose the use of a Kalman filter to estimate the position of vehicles relative to lanes by vehicle states on the basis of a vehicle–road micro traffic model in the world coordinate system. The central position of the ROI is determined through a combination of optimal preview time theory with the ROI prediction. The range of the ROI is determined by offsetting upward, downward, leftward, and rightward from the central position of the ROI. The left and right ROI are processed separately to detect lane lines. Simulation results show that the proposed prediction method reduces the ROI range, and the model predictive control controller can make the vehicle run smoothly from the initial position to the road centerline.
RETURN CONTROL OF ELECTRONIC POWER STEERING UNEQUIPPED WITH AN ANGLE SEN
Shaosong Li,Luping Guo,Gaojian Cui,Zhixin Yu,Xiaohui Lu,Guodong Wang 한국자동차공학회 2019 International journal of automotive technology Vol.20 No.2
A steering wheel may not be able to return to the center position due to friction torque in its mechanism. Thus, in this study, a return controller is developed to improve the returnability of an electric power steering vehicle without an angle sensor. The aligning moment is well estimated on the basis of a Kalman filter estimator. A trigger rule is also proposed to switch between assist and return controls. Finally, the compensation current for the return control is regulated in accordance with the aligning moment and vehicle speeds. Simulation and real vehicle results show that the proposed control system can significantly improve the returnability of the steering system.
VEHICLE YAW STABILITY CONTROL AT THE HANDLING LIMITS BASED ON MODEL PREDICTIVE CONTROL
Shaosong Li,Guodong Wang,Bangcheng Zhang,Zhixin Yu,Gaojian Cui 한국자동차공학회 2020 International journal of automotive technology Vol.21 No.2
This study proposes a double linear model predictive control (DLMPC) structure to improve the tyre force utilization of active front steering (AFS) vehicle at the handing limits. The DLMPC structure consists of a linear model predictive control (LMPC) and a linear time-varying model predictive control (LTV-MPC). During normal driving conditions, the AFS adopts LMPC to control the vehicle. When vehicle running at the handing limits, the tyre force is near saturation, LTV-MPC is activated to prevent tyre force from entering unstable region. The proposed DLMPC controller can reflect the nonlinear dynamic characteristic of tyres by the expression design of tyre force. Double lane change and sine with dwell maneuver tests are provided to demonstrate the effectiveness and feasibility of the DLMPC controller. Results corroborate that the proposed DLMPC controller can fully exploit the potential of AFS and maintain the yaw stability of the vehicle at the handling limits.