• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.5
• /
• pp.257-263
• /
• 2022

Active stabilizers use signals such as steering angle, yaw rate, and lateral acceleration to vary the roll stiffness of the front and rear suspension depending on the vehicle's driving conditions, and are attracting attention as RSC (Roll Stability Control) system that suppresses roll when turning and improves ride comfort when going straight. Various studies have been conducted in relation to active stabilizer bars and RSC systems. However, accurate modeling of passive stabilizer model and active stabilizer model and vehicle dynamics analysis result verification are insufficient, and performance result analysis related to vehicle roll angle estimation and electric motor control is insufficient. Therefore, in this study, an accurate vehicle dynamics model was constructed by measuring the passive/active stabilizer bar model and component parameters. Based on this, the analysis result with high reliability was derived by comparing the roll angle estimation algorithm based on the lateral acceleration and suspension of the vehicle with the actual vehicle driving test result. In addition, it was intended to accurately analyze the motor torque characteristics and roll reduction effects of the electric motor-driven RSC system.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.17 no.4
• /
• pp.70-75
• /
• 2018

This paper describes an Integrate Dynamic Control system with Brake System (IDCB) for SUV vehicles. The system was developed to stabilize the lateral dynamics, maintain the steerability and improve the ride comfort on various roads. A fuzzy logic control method is used to design the IDCB. The performance of the IDCB is validated under different road and driving conditions. The results show that the IDCB tracks the reference yaw rate under all tested conditions; in addition, it reduces the body slip angle and roll angle. When a vehicle runs on a split-${\mu}$ road and a brake input is applied, the IDCB virtually eliminates the lateral dynamics. Thus, the IDCB improves the lateral stability, preserves the steerability and enhances the ride comfort of vehicles.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.636-639
• /
• 1997

In this paper, a dynamic control scheme is proposed which not only compensates for the lateral dynamics and longitudinal dynamics but also deal with the yaw motion dynamics. Using the dynamic control technique, adaptive and learning algorithm together, the proposed controller is not only robust to disturbance and parameter uncertainties but also can learn the inverse dynamics model in steady state. Based on the proposed dynamic control scheme, a dynamic vehicle simulator is contructed to design and test various control techniques for 4-wheel steering vehicles.

• Journal of Drive and Control
• /
• v.17 no.1
• /
• pp.13-20
• /
• 2020

Adaptive neural networks based lateral controller is presented to guarantee path following performance for vehicle lane keeping in the presence of parameter time-varying characteristics of the vehicle lateral dynamics due to the road surface condition, load distribution, tire pressure and so on. The proposed adaptive controller could compensate vehicle lateral dynamics deviated from nominal dynamics resulting from parameter variations by incorporating it with neural networks that have the ability to approximate any given nonlinear function by adjusting weighting matrices. The controller is derived by using Lyapunov-based approach, which provides adaptive update rules for weighting matrices of neural networks. To show the superiority of the presented adaptive neural networks controller, the simulation results are given while comparing with backstepping controller chosen as the baseline controller. According to the simulation results, it is shown that the proposed controller can effectively keep the vehicle tracking the pre-given trajectory in high velocity and curvature with much accuracy under parameter variations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.21 no.3
• /
• pp.179-186
• /
• 2015

In this paper, a novel lateral control system is proposed for the purpose of improving lane keeping performance which is independent from GPS signals. Lane keeping is a key function for the realization of unmanned driving systems. In order to obtain this objective, a vision sensor based real-time lane detection scheme is developed. Furthermore, we employ a data fusion along with a real-time steering angle of the test vehicle to improve its lane keeping performance. The fused direction data can be obtained by an IMU sensor and vision sensor. The performance of the proposed system was verified by computer simulations along with field tests using MOHAVE, a commercial vehicle from Kia Motors of Korea.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.21 no.5
• /
• pp.54-58
• /
• 2013

In recent days, vehicles have become equipped with electric systems that assist and help drivers driving safe by reducing possible accidents. LDWS(Lane Departure Warning System) and LKAS(Lane Keeping Assistant System) are involved in assist systems, especially for lateral motion of vehicles. Sudden and inattentive lateral motion of vehicles due to drivers' fatigue, illness, inattention, and drowsiness are major causes of accidents in highway. LDWS and LKAS provide drivers with warnings or assisting power to reduce any possibilities of accidents. In order to prevent or minimize the possibilities of accidents, lateral motion control of vehicles has been introduced in this research. DGPS/RTK(Differential Global Positioning System/Real Time Kinematics) and GIS(Geographic Information System) have been used to obtain the current position of vehicles and decide when activate controlling lateral motion of vehicles. The presented lateral motion control has been validated with actual vehicle tests.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.15 no.6
• /
• pp.120-127
• /
• 2007

This paper describes the development of a nonlinear observer for four wheel steer (4WS) vehicle. An observer is designed to estimate the vehicle variables difficult to measure directly. A brake yaw motion controller (BYMC), which uses a PID control method, is also proposed for controlling the brake pressure of the rear and inner wheels to enhance lateral stability. It induces the yaw rate to track the reference yaw rate, and it reduces a slip angle on a slippery road. The braking and steering performances of the anti-lock brake system (ABS) and BYMC are evaluated for various driving conditions, including straight, J-turn, and sinusoidal maneuvers. The simulation results show that developed ABS reduces the stopping distance and increases the longitudinal stability. The observer estimates velocity, slip angle, and yaw rate of 4WS vehicle very well. The results also reveal that the BYMC improves vehicle lateral stability and controllability when various steering inputs are applied.

• Proceedings of the KSME Conference
• /
• 2001.06b
• /
• pp.565-570
• /
• 2001

Vehicle dynamics control (VDC) system requires more information on driving conditions compared with ABS and/or TCS. In order to develop the VDC system, tire slip angles, vehicle side-slip angle, and vehicle lateral velocity as well as road friction coefficient are needed. Since there are not any cheap and reliable sensors, recent researches on parameter estimation have given rise to a number of parameter estimation techniques. This paper presents new vehicle model to estimate vehicle's yaw rate. This model is improved from the conventional 2 degrees of freedom vehicle model, so-called bicycle model, taking nonlinear effects into account. These nonlinear effects are: (i) tyre nonlinearity; (ii) lateral load transfer during cornering; (iii) variable gear ratio with respect to vehicle velocity. Estimation results are validated with the experimental results.

• Journal of the Korean Society of Industry Convergence
• /
• v.22 no.5
• /
• pp.575-582
• /
• 2019

Advanced driving assist system can support safety of driver and passengers which may require vehicle dynamics states as well as road geometry. It is essential to have in real-time estimation of related variables and parameters. Among the road geometry parameters, road slope angle which can not be measured is essential parameter in pose estimation, adaptive cruise control and others on sag road. In this paper, Kalman filter based method for the estimation of the vehicle dynamics and road slope angle using a nonlinear vehicle model is proposed. It uses a combination of Kalman filter as Cascade Extended Kalman Filter. CEKF uses measured vehicle states such as yaw rate, longitudinal/lateral acceleration and velocity. Unknown vehicle parameters such as center of gravity and inertia are obtained by 2 D.O.F lateral model and experimentally. Simulation and Experimental tests conducted with commercialized vehicle dynamics model and real-car.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.4
• /
• pp.38-46
• /
• 2011

This paper presents roll angle estimator which used Kalman filter. Recently, the uses of the ELSD (Electronic Limited Slip Differential) and TVD(Torque Vectoring Differential) for vehicle yaw control are studied in many researches. However the roll angle can be negative effect of ELSD and TVD control. Therefore the information of roll angle can be used for vehicle yaw control. Moreover it can be used for rollover prevent control. Recently, most of the vehicles use lateral acceleration and yaw rate sensor. In this paper, design of Kalman filter which used lateral acceleration and yaw rate information is developed. In this paper, in order to verify the estimator ability, the CarSim and Matlab/Simulink are used.