Vehicle Stability Control on Tire Burst Steering and Braking Condition With Active Steering System

2018 ◽  
Author(s):  
Yaqi Dai ◽  
Jian Song ◽  
Liangyao Yu
Keyword(s):  
Control Strategy ◽  
Steering System ◽  
Stability Control ◽  
Steering Angle ◽  
Tire Force ◽  
Vehicle Stability Control ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Control Layer ◽  
Yaw Moment

By analyzing the key safety problems under the front-outside-tire burst steering condition, a vehicle stability control strategy is proposed in this paper, which is based on active front steering and differential braking systems. Taken both the handling stability and safety into account, we divided the whole control strategy into two layers, which are yaw moment control layer and the additional steering angle & tire force distribution layer. To solve the similar linear problem concisely, the LQR control is adopted in the yaw moment control layer. To achieve the goal of providing enough additional lateral force and yaw moment while keeping the burst tire in appropriate condition, the additional steering angle provided by active front steering system and the tire force distribution was adjusted step by step. To test the proposed control strategy performance, we modelling a basic front-outside-tire burst steering condition, in which the tire blows out once the vertical pressure reach the predefined critical value. Through simulation on different adhesion coefficient road, the control strategy proposed in this paper performance quite better compare with the uncontrolled one in aspect of movement, burst tire protection, handling stability.

scholarly journals Game-Based Hierarchical Cooperative Control for Electric Vehicle Lateral Stability via Active Four-Wheel Steering and Direct Yaw-Moment Control

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3339 ◽  
Author(s):  
Zhao ◽  
Lu ◽  
Zhang
Keyword(s):  
Electric Vehicle ◽  
Control Strategy ◽  
Cooperative Control ◽  
Stackelberg Game ◽  
Stability Control ◽  
Lateral Stability ◽  
Direct Yaw Moment Control ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Yaw Moment

A Stackelberg game-based cooperative control strategy is proposed for enhancing the lateral stability of a four-wheel independently driving electric vehicle (FWID-EV). An upper‒lower double-layer hierarchical control structure is adopted for the design of a stability control strategy. The leader‒follower-based Stackelberg game theory (SGT) is introduced to model the interaction between two unequal active chassis control subsystems in the upper layer. In this model, the direct yaw-moment control (DYC) and the active four-wheel steering (AFWS) are treated as the leader and the follower, respectively, based on their natural characteristics. Then, in order to guarantee the efficiency and convergence of the proposed control strategy, a sequential quadratic programming (SQP) algorithm is employed to solve the task allocation problem among the distributed actuators in the lower layer. Also, a double-mode adaptive weight (DMAW)- adjusting mechanism is designed, considering the negative effect of DYC. The results of cosimulation with CarSim and Matlab/Simulink demonstrate that the proposed control strategy can effectively improve the lateral stability by properly coordinating the actions of AFWS and DYC.

Path tracking framework synthesizing robust model predictive control and stability control for autonomous vehicle

2020 ◽  
Vol 234 (9) ◽  
pp. 2330-2341
Author(s):  
Jiaxing Yu ◽  
Xiaofei Pei ◽  
Xuexun Guo ◽  
JianGuo Lin ◽  
Maolin Zhu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Stability Control ◽  
Robust Model Predictive Control ◽  
Direct Yaw Moment Control ◽  
Robust Model ◽  
Yaw Moment Control ◽  
Moment Control ◽  
The Stability ◽  
Yaw Moment

This paper proposes a framework for path tracking under additive disturbance when a vehicle travels at high speed or on low-friction road. A decoupling control strategy is adopted, which is made up of robust model predictive control and the stability control combining preview G-vectoring control and direct yaw moment control. A vehicle-road model is adopted for robust model predictive control, and a robust positively invariant set calculated online ensures state constraints in the presence of disturbances. Preview G-vectoring control in stability control generates deceleration and acceleration based on lateral jerk, later acceleration, and curvature at preview point when a vehicle travels through a cornering. Direct yaw moment control with additional activating conditions provides an external yaw moment to stabilize lateral motion and enhances tracking performance. A comparative analysis of stability performance of stability control is presented in simulations, and furthermore, many disturbances are considered, such as varying wind, road friction, and bounded state disturbances from motion planning and decision making. Simulation results show that the stability control combining preview G-vectoring control and direct yaw moment control with additional activating conditions not only guarantees lateral stability but also improves tracking performance, and robust model predictive control endows the overall control system with robustness.

Vehicle Direct Yaw Moment Control with Longitudinal Forces Distribution

2014 ◽  
Vol 709 ◽  
pp. 331-334
Author(s):  
Man Hong Huang ◽  
Huan Shen ◽  
Yun Sheng Tan
Keyword(s):  
Control System ◽  
Reference Model ◽  
Sliding Mode ◽  
Stability Control ◽  
Yaw Rate ◽  
Vehicle Stability Control ◽  
Braking Torque ◽  
Stability Control System ◽  
Yaw Moment Control ◽  
Yaw Moment

In this paper, a vehicle stability control system is proposed to improve vehicle comfort, handling and stability. The control system includes reference model, DYC controller and Distributer. Reference model is used to obtain the desired yaw rate. DYC controller determines the desired yaw moment by means of sliding-mode technique. Distributer, based on maneuverability and comfort, distributes driving torque or braking torque according to the desired yaw rate. Simulation result shows that the proposed control algorithm can improve vehicle handling and stability effectively.

1110 Study on Yaw Moment Control of Electric Vehicle by Balancing Three Tire Force Usages as Braking and Cornering

2008 ◽  
Vol 2008.17 (0) ◽  
pp. 143-146 ◽  
Author(s):  
Shogo KANAGAWA ◽  
Takayoshi KAMADA ◽  
Masao NAGAI ◽  
Nobuo MASAKI ◽  
Haruo IWANO
Keyword(s):  
Electric Vehicle ◽  
Tire Force ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Yaw Moment

Integrated nonlinear robust adaptive control for active front steering and direct yaw moment control systems with uncertainty observer

2020 ◽  
Vol 42 (16) ◽  
pp. 3267-3280
Author(s):  
Jiaxu Zhang ◽  
Shiying Zhou ◽  
Fengjun Li ◽  
Jian Zhao
Keyword(s):  
Adaptive Controller ◽  
Steering System ◽  
Front Wheel ◽  
Robust Adaptive Control ◽  
Direct Yaw Moment Control ◽  
Yaw Moment Control ◽  
Moment Control ◽  
Robust Adaptive ◽  
Yaw Moment ◽  
Nonlinear Robust

This paper presents an integrated nonlinear robust adaptive controller with uncertainty observer for active front wheel steering system and direct yaw moment control system. First, an integrated vehicle chassis control model is established as the nominal model with the additive and multiplicative uncertainties of the system. Secondly, an integrated nonlinear robust adaptive control law with the additive uncertainty observer is designed via Lyapunov stability theory to calculate the corrective yaw moment, and an adaptive law is designed based on projection correction method to online estimate and compensate the multiplicative uncertainty of the system. Then, the constrained optimal allocation problem of the corrective yaw moment is transformed into the nonlinear optimization problem, and the sequential quadratic programming method is used to solve the nonlinear optimization problem to coordinate active front wheel steering system and direct yaw moment control system. Finally, the performance of the proposed integrated nonlinear robust adaptive controller is verified via vehicle dynamics simulation software.

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