Integrated Control of Tire Normal Forces and Active Front Steering to Enhance Vehicle Handling

2005 ◽  
Author(s):  
Carl March ◽  
Taehyun Shim ◽  
Yi Zhang
Keyword(s):  
Normal Force ◽  
Integrated Control ◽  
Vehicle Handling ◽  
Normal Forces ◽  
Yaw Rate ◽  
Integrated Chassis Control ◽  
Active Front Steering ◽  
Management Scheme ◽  
Control Scheme ◽  
Chassis Control

This paper presents the development of an active front steering (AFS) control system and normal force control (NFC) scheme utilizing fuzzy reasoning to track neutral steer yaw rate. The performance of the stand-alone controllers is compared with an integrated chassis management scheme combining the two. The simulation results indicate that the NFC by the active suspension as a stand-alone system shows improvement in vehicle handling response. The integrated chassis control scheme utilizing the steering and suspension controllers is proven to be more effective in attaining the desired performance that would not be attained individually.

Development of Integrated Chassis Control System for Vehicle Handling Enhancement

2008 ◽  
Author(s):  
Chinar Ghike ◽  
Taehyun Shim
Keyword(s):  
Control System ◽  
Tire Model ◽  
Vehicle Handling ◽  
Integrated Chassis Control ◽  
Nonlinear Predictive Control ◽  
Moment Distribution ◽  
Control Scheme ◽  
Wheel Torque ◽  
Chassis Control ◽  
Vehicle Motion

Various active chassis control systems have been developed to improve vehicle handling and stability. Brake-based electronic stability programs and advanced driveline technologies can distribute different wheel torque to all four wheels to regulate vehicle motion. Active front and rear steer systems are widely used to control the vehicle yaw rate and side slip responses. In addition, active anti-roll bars can improve vehicle handling by adjusting roll moment distribution. This paper proposes an integrated chassis control scheme that combines these individual systems using nonlinear predictive control theory. An 8 degree-of-freedom vehicle model is used with a Magic Formula tire model for controller development. The performance of proposed controller is compared to individual control system through simulation and shows significant improvement in vehicle handling.

Composite Nonlinear Feedback Control with Multi-objective Particle Swarm Optimization for Active Front Steering System

2015 ◽  
Vol 72 (2) ◽  
Author(s):  
Liyana Ramli ◽  
Yahaya Md. Sam ◽  
Zaharuddin Mohamed ◽  
M. Khairi Aripin ◽  
M. Fahezal Ismail
Keyword(s):  
Parameter Estimation ◽  
Particle Swarm Optimization ◽  
Nonlinear Feedback ◽  
Nonlinear Gain ◽  
Composite Nonlinear Feedback ◽  
Swarm Optimization ◽  
Vehicle Handling ◽  
Multi Objective ◽  
Yaw Rate ◽  
Active Front Steering

The purpose of controlling the vehicle handling is to ensure that the vehicle is in a safe condition and following its desire path. Vehicle yaw rate is controlled in order to achieve a good vehicle handling. In this paper, the optimal Composite Nonlinear Feedback (CNF) control technique is proposed for an Active Front Steering (AFS) system for improving the vehicle yaw rate response. The model used in order to validate the performance of controller is nonlinear vehicle model with 7 degree-of-freedom (DOF) and a bicycle model is implemented for the purpose of designing the controller. In designing an optimal CNF controller, the parameter estimation of linear and nonlinear gain becomes very important to produce the best output response. An intelligent algorithm is designed to minimize the time consumed to get the best parameter. To design an optimal method, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize the CNF controller performance. As a result, transient performance of the yaw rate has improved with the increased speed of in tracking and searching of the best optimized parameter estimation for the linear and the nonlinear gain of CNF controller.  

MPC Based Integrated Chassis Control to Enhance Vehicle Handling Considering Roll Stability

2011 ◽  
Author(s):  
Ganesh Adireddy ◽  
Taehyun Shim
Keyword(s):  
Control System ◽  
High Speed ◽  
Control Method ◽  
Torque Distribution ◽  
Vehicle Handling ◽  
Integrated Chassis Control ◽  
Wheel Torque ◽  
Vehicle Rollover ◽  
Chassis Control ◽  
Vehicle Chassis

An integrated vehicle chassis control system was developed to improve vehicle handling (yaw) responses while maintain vehicle roll stability using an 8 DOF vehicle model, a simplified tire model, and a model predictive control method. The proposed control system incorporates active wheel torque distribution, active front steering, and active anti-rollbar to enhance vehicle handling and its ability to track the desired trajectory when the risk of vehicle rollover is low. As vehicle rollover risks increase, the proposed control system shifts its control focus from only handling enhancement to vehicle roll stabilization by adjusting the gains in the controller. The simulation results show that the proposed control system can improve vehicle handling responses while ensuring vehicle roll stability at high speed vehicle maneuvers.

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 Study on Integrated Control of Active Front Steering and Direct Yaw Moment Based on Vehicle Lateral Velocity Estimation

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Tao Sun ◽  
Hao Guo ◽  
Jian-yong Cao ◽  
Ling-jiang Chai ◽  
Yue-dong Sun
Keyword(s):  
Integrated Control ◽  
Front Wheel ◽  
Velocity Estimation ◽  
Extended Kalman Filtering ◽  
Lateral Velocity ◽  
Sideslip Angle ◽  
Yaw Rate ◽  
Active Front Steering ◽  
Fuzzy Control Algorithm ◽  
Yaw Moment

Considering the vehicle lateral velocity is difficult to be measured at integration of chassis control in configuration of production vehicle, this study presents the vehicle lateral velocity estimation based on the extended Kalman filtering with the standard sensor information. The fuzzy control algorithm is proposed to integrate direct yaw moment control and active front steering with lateral velocity estimation. The integration controller produces direct yaw moment and front wheel angle compensation to control yaw rate and sideslip angle, which makes the actual vehicle yaw rate and sideslip angle follow desirable yaw rate and desirable sideslip angle. The simulation results show vehicle handling and stability are enhanced under different driving cycles by the proposed algorithm.

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