• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.4
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• pp.173-179
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• 2003

In this paper, a real-time multibody vehicle dynamics and control model has been developed for a virtual reality intelligent vehicle simulator. The simulator consists of low PCs for a virtual reality visualization system, vehicle dynamics and control analysis system a control loading system, and a network monitoring system. Virtual environment is created by 3D Studio Max graphic tool and OpenGVS real-time rendering library. A real-time vehicle dynamics and control model consists of a control module based on the sliding mode control for adaptive cruise control and a real-time multibody vehicle dynamics module based on the subsystem synthesis method. To verify the real-time capability of the model, cut-in, cut-out simulations have been carried out.

• Journal of Mechanical Science and Technology
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• v.19 no.4
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• pp.985-992
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• 2005

Vehicle Stability Control (VSC) system prevents vehicle from spinning or drifting out mainly by braking intervention. Although a control threshold of conventional VSC is designed by vehicle characteristics and centered on average drivers, it can be a redundancy to expert drivers in critical driving conditions. In this study, a manual adaptation of VSC is investigated by changing the control threshold. A control threshold can be determined by phase plane analysis of side slip angle and angular velocity which is established with various vehicle speeds and steering angles. Since vehicle side slip angle is impossible to be obtained by commercially available sensors, a side slip angle is designed and evaluated with test results. By using the estimated value, phase plane analysis is applied to determine control threshold. To evaluate an effect of control threshold, we applied a 23-DOF vehicle nonlinear model with a vehicle planar motion model based sliding controller. Controller gains are tuned as the control threshold changed. A VSC with various control thresholds makes VSC more flexible with respect to individual driver characteristics.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.37-43
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• 2013

This paper describes an investigation into coordinated control of electronic stability control (ESC) and active roll control system (ARS). The coordinated control is suggested to improve the vehicle stability and agility features by yaw rate control. The proposed integrated chassis control algorithm consists of a supervisor, control algorithms, and a coordinator. The supervisor monitors the vehicle status and determines desired vehicle motions such as a desired yaw rate and desired roll motion based on control modes to improve vehicle stability. According to the corresponding the desired vehicle dynamics, the control algorithm calculated a desired yaw moment and desired roll moment, respectively. Based on the desired yaw moment and the desired roll moment, the coordinator determines the brake pressures and the ARC motor torques based on control strategies. Closed loop simulations with a driver-vehicle-controller system were conducted to investigate the performance of the proposed control strategy using CarSim vehicle dynamics software and the integrated controller coded using Matlab/Simulink.

• Journal of Engineering Education Research
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• v.15 no.4
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• pp.48-52
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• 2012

The purpose of this paper is to design and implement the user motion pattern control system for the simulated vehicle. After analyzing the user motion patterns in the system, the patterns are used to control the moving direction of the simulated vehicle such as forward, backward, turn right, turn left etc. The patterns in the system around are sent to the simulated vehicle in real time. In order to execute the suggested user motion pattern control system, the Kinect is used for executing the system. The Kinect recognizes the specified user motion patterns and it transmits the data to the user motion pattern control system. There are nine kinds of the user motion patterns in the system for controlling the simulated vehicle. In addition to this, some sensors are used to detect the condition of the simulated vehicle. GPS is also used to estimate the current location of the simulated vehicle and to obtain the driving information.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.875-882
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• 2007

In order for a vehicle to follow a predetermined trajectory accurately, its position must be estimated accurately and reliably. In this thesis, we propose trajectory tracking control methods for unmanned vehicle and a positioning system using ultrasonic wave. The positioning problem is an important part of control problem for unmanned navigation of a vehicle. Dead Reckoning is widely used for positioning of vehicle. However this method has problems because it accumulates estimation errors. We propose a new method to increase the accuracy of position estimation using the Ultrasonic Satellite System (USAT). It is shown that we will be able to estimate the position of vehicle precisely, in which errors are not accumulated. And proposed trajectory tracking control methods include both a new path planning method and a lateral control method for vehicle. The experimental results show that the proposed methods enables exact vehicle trajectory tracking even under various environmental factors.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.9
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• pp.146-157
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• 1999

Safety systems for road vehicles have been rapidly developed in recent years. Especially, the VDC(Vehicle dynamics Control) system is a new active safety system for road vehicles which controls its dynamic vehicle motion in emergency situations . In the case of configuring the VDC system by utilizing the ABS(Anti-lock Brake System), the role of a control logic which directly influences the vehicle motion is very important. In this study the performance of the VDC vehicle was compared to the performances of the CBS (Conventional Brake system )and ABS vehicle. For various driving conditions , the simulation of vehicle dynamics with known VDC control logics was performed. Analysis results showed the VDC vehicle could stably perform even on the road of low coefficient of friction. In addition it was shown that the basic control logic for the VDC system could outstandingly improve driving stability in the case of braking as well as constant speed cruising.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.129-139
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• 2010

To be satisfied with complex load condition of electric vehicle, fuzzy logic control (FLC) is applied to improve speed response and system robust performance of induction traction machine based on indirect rotor field orientation control. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels of lightweight electric vehicle by means the vehicle used for passenger transportation. The electronic differential system ensures the robust control of the vehicle behavior on the road. It also allows controlling, independently, every driving wheel to turn at different speeds in any curve. Our electric vehicle fuzzy inference system control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency and the robustness of the proposed control with good performances compared with the traditional PI speed control, the FLC induction traction machine presents not only good steady characteristic, but with no overshoot too.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.649-659
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• 2016

This paper describes control algorithm and control structure of vehicle control unit for range-extended electric vehicle equipped with engine-generator system, and specially presents methods which determine optimal operating points and decreases a vibration or a shock for operating the engine-generating system. The vehicle control algorithm is consisted of several parts which are sequence control, calculation of wheel demand torque, determination of operating points, and management of operating points and so vehicle controller has be made possible to efficiently manage calibration parameters. The control algorithm is evaluated by driving test modes, launching performance and operating engine-generator system and so on. In conclusion, this paper present methods for extending a mileage, improving a launching performance and reducing vibration or shock when the engine-generating system is starting or is stopping.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.4
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• pp.121-128
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• 2000

In this paper, the control algorithm fur an autonomous vehicle is studied and applied to an actual 2 wheel-driven vehicle system. In order to control a nonholonomic system, the kinematic model for an autonomous vehicle is constructed by relative velocity relationship about the virtual point at distance from the vehicle's frame. And the optimal controller that based on the kinematic model is operated on purpose to track a reference vehicle's path. The actual system is designed with named 'HYAVI' and the system controller is applied. Because all the results of simulation don't satisfy the driving conditions of HYAVI, a reformed control algorithm that satisfies an actual autonomous vehicle is applied at HYAVI. At the results of actual experiments, the path tracking works very well by the reformed control algorithm. An autonomous vehicle that applied this control algorithm can be easily used for a path generation algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.932-937
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• 2003

In this paper, we will explain about the unmanned vehicle control and modeling for combined obstacle avoidance and lane tracking. First, obstacle avoidance is considered as one of the important technologies in the unmanned vehicle. It is consisted by two parts: the first part includes the longitudinal control system for the acceleration and deceleration and the second part is the lateral control system for the steering control. Each system uses to the obstacle avoidance during the vehicle moving. Therefore, we propose the method of vehicle control, modeling and obstacle avoidance. Second, we describe a method of lane tracking by means of vision system. It is important in the unmanned vehicle and mobile robot system. In this paper, we deal with lane tracking and image processing method and it is including lane detection method, image processing algorithm and filtering method.