scholarly journals Integrated Chassis Control of Active Front Steering and Yaw Stability Control Based on Improved Inverse Nyquist Array Method

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Bing Zhu ◽  
Yizhou Chen ◽  
Jian Zhao
Keyword(s):  
Reference Model ◽  
Stability Control ◽  
Response Analysis ◽  
Vehicle Model ◽  
Stability Performance ◽  
Integrated Chassis Control ◽  
Active Front Steering ◽  
Yaw Stability ◽  
Chassis Control ◽  
The Stability

An integrated chassis control (ICC) system with active front steering (AFS) and yaw stability control (YSC) is introduced in this paper. The proposed ICC algorithm uses the improved Inverse Nyquist Array (INA) method based on a 2-degree-of-freedom (DOF) planar vehicle reference model to decouple the plant dynamics under different frequency bands, and the change of velocity and cornering stiffness were considered to calculate the analytical solution in the precompensator design so that the INA based algorithm runs well and fast on the nonlinear vehicle system. The stability of the system is guaranteed by dynamic compensator together with a proposed PI feedback controller. After the response analysis of the system on frequency domain and time domain, simulations under step steering maneuver were carried out using a 2-DOF vehicle model and a 14-DOF vehicle model by Matlab/Simulink. The results show that the system is decoupled and the vehicle handling and stability performance are significantly improved by the proposed method.

scholarly journals Design of an Integrated Vehicle Chassis Control System with Driver Behavior Identification

2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Bing Zhu ◽  
Yizhou Chen ◽  
Jian Zhao ◽  
Yunfu Su
Keyword(s):  
Control System ◽  
Control Strategy ◽  
Driver Behavior ◽  
Stability Performance ◽  
Integrated Chassis Control ◽  
Yaw Moment Control ◽  
Chassis Control ◽  
Lane Change Test ◽  
Behavior Characteristics ◽  
Vehicle Chassis

An integrated vehicle chassis control strategy with driver behavior identification is introduced in this paper. In order to identify the different types of driver behavior characteristics, a driver behavior signals acquisition system was established using the dSPACE real-time simulation platform, and the driver inputs of 30 test drivers were collected under the double lane change test condition. Then, driver behavior characteristics were analyzed and identified based on the preview optimal curvature model through genetic algorithm and neural network method. Using it as a base, an integrated chassis control strategy with active front steering (AFS) and direct yaw moment control (DYC) considering driver characteristics was established by model predictive control (MPC) method. Finally, simulations were carried out to verify the control strategy by CarSim and MATLAB/Simulink. The results show that the proposed method enables the control system to adjust its parameters according to the driver behavior identification results and the vehicle handling and stability performance are significantly improved.

Composite Nonlinear Feedback for Vehicle Active Front Steering

2014 ◽  
Vol 663 ◽  
pp. 127-134 ◽  
Author(s):  
M.H. Che Hasan ◽  
Y.M. Sam ◽  
Ke Mao Peng ◽  
Muhamad Khairi Aripin ◽  
Muhamad Fahezal Ismail
Keyword(s):  
Control Method ◽  
Actuator Saturation ◽  
External Disturbance ◽  
Reference Signal ◽  
Stability Control ◽  
Nonlinear Feedback ◽  
Composite Nonlinear Feedback ◽  
Active Front Steering ◽  
Yaw Stability ◽  
Fast Settling

In this paper, Composite Nonlinear Feedback (CNF) is applied on Active Front Steering (AFS) system for vehicle yaw stability control in order to have an excellent transient response performance. The control method, which has linear and nonlinear parts that work concurrently capable to track reference signal very fast with minimum overshoot, fast settling time, and without exceed nature of actuator saturation limit. Beside, modelling of 7 degree of freedom for typical passenger car with magic formula to represent tyre nonlinearity behaviour is also presented to simulate controlled vehicle as close as possible with a real situation. An extensive computer simulation is performed with considering a various profile of cornering manoeuvres with external disturbance to evaluate its performance in different scenarios. The performance of the proposed controller is compared to conventional Proportional Integration and Derivative (PID) for effectiveness analysis.

Research on Yaw Stability Control of Active Front Steering Based on BP Neural Network PID

2013 ◽  
Vol 765-767 ◽  
pp. 1903-1907
Author(s):  
Jie Wei ◽  
Guo Biao Shi ◽  
Yi Lin
Keyword(s):  
Neural Network ◽  
Bp Neural Network ◽  
Pid Controller ◽  
Steering System ◽  
Stability Control ◽  
Steering Angle ◽  
System A ◽  
Active Front Steering ◽  
Yaw Stability ◽  
Neural Network Pid

This paper proposes using BP neural network PID to improve the yaw stability of the vehicle with active front steering system. A dynamic model of vehicle with active front steering is built firstly, and then the BP neural network PID controller is designed in detail. The controller generates the suitable steering angle so that the vehicle follows the target value of the yaw rate. The simulation at different conditions is carried out based on the fore established model. The simulation results show the BP neural network PID controller can improve the vehicles yaw stability effectively.

Optimal Composite Nonlinear Feedback Controller for an Active Front Steering System

2014 ◽  
Vol 554 ◽  
pp. 526-530 ◽  
Author(s):  
Liyana Ramli ◽  
Yahya M. Sam ◽  
Zaharuddin Mohamed ◽  
Muhamad Khairi Aripin ◽  
Muhamad Fahezal Ismail
Keyword(s):  
Parameter Optimization ◽  
Optimization Problems ◽  
Steering System ◽  
Stability Control ◽  
Feedback Controller ◽  
Nonlinear Feedback ◽  
Composite Nonlinear Feedback ◽  
Fast Tracking ◽  
Active Front Steering ◽  
Yaw Stability

Yaw stability control is the most popular topics in the automotive field. Several studies have been done in searching the effective method in controlling yaw moment. Hence, an integration of the active front steering system (AFS) with Composite Nonlinear Feedback controller is presented in this paper. Recently, this controller has been used by a lot of researchers in controlling their system performance due to its main advantage that can be seen in transient response which demonstrate super fast tracking. An optimal CNF feedback control problem is formulated as a parameter optimization problem with performance index and restrictions on stability. To handle such restrictions and constraint, the particle swarm optimization algorithm is applied to solve parameter optimization problems.

Estimation of Vehicle Sideslip Angle Using Strong Tracking SRUKF

2014 ◽  
Vol 614 ◽  
pp. 267-270
Author(s):  
Jian Feng Chen ◽  
Xiao Dong Sun ◽  
Long Chen ◽  
Hao Bin Jiang
Keyword(s):  
Numerical Simulations ◽  
High Speed ◽  
State Observer ◽  
Stability Control ◽  
Vehicle Model ◽  
Sideslip Angle ◽  
Magic Formula ◽  
The Stability ◽  
Accuracy Performance ◽  
Better Than

Sideslip angle is an important parameter for the stability control of high-speed vehicles. In this paper, a novel state observer based on strong tracking SRUKF is presented to estimate the sideslip angle. Besides the strong tracking SRUKF algorithm, a 2-DOF vehicle model and a “Magic Formula” are utilized to construct the state observer. Numerical simulations are implemented to testify on the accuracy performance of estimation based on the strong tracking SRUKF and standard UKF. The results show that the trends using two types of filters are accordant with the theoretic values, and the accuracy of the former is better than the latter.

Vehicle yaw stability control using active rear steering: Development and experimental validation

2016 ◽  
Vol 231 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Baozhen Zhang ◽  
Amir Khajepour ◽  
Avesta Goodarzi
Keyword(s):  
Cost Effective ◽  
Steering System ◽  
Stability Control ◽  
Vehicle Stability ◽  
Stability Performance ◽  
Active Steering ◽  
Vehicle Stability Control ◽  
Yaw Stability ◽  
Suspension Model ◽  
Vehicle Testing

In this paper, a novel pulse active steering system for improving vehicle yaw stability is developed. In the proposed method, pulses are sent to the steerable rear wheels whenever the error between the expected and actual yaw rate is outside a predetermined range. The proposed method and its performance are verified experimentally by full vehicle testing. For this purpose, a simplified vehicle model and a rear suspension model are developed. Vehicle stability is investigated and the steering pulse parameters on the vehicle’s stability are studied. A control system is designed and numerical simulations are performed. Moreover, the active rear steering system is implemented on a Lexus for performing road experiments. Results from simulations and experiments indicate that considerable improvement in the yaw stability performance can be achieved by the proposed system. The proposed method is more cost effective and simpler for vehicle stability control.

Vehicle Yaw Stability Control by Coordinated Active Front Steering and Differential Braking in the Tire Sideslip Angles Domain

2013 ◽  
Vol 21 (4) ◽  
pp. 1236-1248 ◽  
Author(s):  
Stefano Di Cairano ◽  
Hongtei Eric Tseng ◽  
Daniele Bernardini ◽  
Alberto Bemporad
Keyword(s):  
Stability Control ◽  
Active Front Steering ◽  
Yaw Stability
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