• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.9 s.252
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• pp.1154-1159
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• 2006

In this paper, time-frequency analysis and multi-dimensional spectral analysis methods are applied to source identification and diagnostic of non-stationary sound vibration signals. By checking the coherences for concerned time, this simulation is very well coincident to expected results. The proposed method analyzes the signal instantaneously in both time and frequency domains. The MDSA (Multiple Dimensional Spectral Analysis) analyzes the signal in the plane of instantaneous time and instantaneous frequency at the same time. And it was verified by using the 1500cc passenger car which is accelerated from 70Hz to 95Hz in 4 seconds, the proposed method is effective in determining the vehicle diagnostic problems.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1346-1353
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• 2007

The simulation analysis of fire-driven flow and passenger evacuation in Daegu subway station, Chung-Ang, have been performed. The first location of outbreak of fire is inside passenger car in the third basement in Chung-Ang station. The smoke flow in the second and third basement has been analyzed using FLUENT 6.2. The CO(carbon monoxide) and temperature distribution in the train units and station platform have been obtained and transferred to input data for evacuation simulation. The highest temperature in the train units was 1500K. For the simulation of passenger evacuation, EXODUS has been used for whole basements (level 1${\sim}$ level 3) in the station. Total number of people was assumed to be one thousand and 640 were placed inside train and 360 were placed outside train. In evacuation simulation, an average of 135 passengers were killed and an average time to evacuate takes 10min 19sec. The main evacuation routes used by passengers were investigated and the cause of death was identified by evacuation simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.1095-1098
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• 2005

Most electronic chassis control systems until today have been designed with optimization on its own performance. However, According to the increase of the interest regarding a vehicle safety and development of information technique, the integration technique of current chassis systems is being emphasized. Each enterprise proposed it with name of GCC(Global Chassis Control) or UCC(Unified Chassis Control). This study realizes control algorithm of suspension and brake by using the vehicle model of low degree of freedom as the primary stage of realization of integrated chassis control system. The proposed algorithm build the simulation environment connected to the CarSim having full vehicle model of 27 degree of freedom for raising the thrust of results

• Journal of Power Electronics
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• v.13 no.4
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• pp.536-545
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• 2013

In this study, an integrated motor control algorithm for an in-wheel electric vehicle is suggested. It consists of slip control that controls the in-wheel motor torque using the road friction coefficient and slip ratio; yaw rate control that controls the in-wheel motor torque according to the road friction coefficient and the yaw rate error; and velocity control that controls the vehicle velocity by a weight factor based on the road friction coefficient and the yaw rate error. A co-simulator was developed, which combined the vehicle performance simulator based on MATLAB/Simulink and the vehicle model of CarSim. Based on the co-simulator, a human-in-the-loop simulation environment was constructed, in which a driver can directly control the steering wheel, the accelerator pedal, and the brake pedal in real time. The performance of the integrated motor control algorithm for the in-wheel electric vehicle was evaluated through human-in-the-loop simulations.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.7
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• pp.595-601
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• 2015

This paper presents an unified chassis control with electronic stability control (ESC) and active front steering (AFS) under lateral force constraint on AFS. When generating the control yaw moment, an optimization problem is formulated in order to determine the tire forces, generated by ESC and AFS. With Karush-Kuhn-Tucker optimality condition, the optimum tire forces can be algebraically calculated. On low friction road, the lateral force in front wheels is easily saturation. When saturated, AFS cannot generate the required control yaw moment. To cope with this problem, new constraint on the lateral tire force is added into the original optimization problem. To check the effectiveness of the propose method, simulation is performed on the vehicle simulation package, CarSim.

• Transactions of the Korean Society of Automotive Engineers
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• v.22 no.1
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• pp.20-28
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• 2014

This paper presents static output feedback LQ and $H_{\infty}$ controllers for rollover prevention. Linear quadratic static output feedback controllers have been proposed for rollover prevention in such a way to minimize the lateral acceleration and the roll angle. Rollover prevention capability can be enhanced if $H_{\infty}$ controller is designed. To avoid full-state measurement for feedback requirement or sensitiveness of an observer to nonlinear model error, static output feedback is adopted. To design static output feedback controllers, Kosut's method is adopted because it is simple to calculate. Differential braking and active anti-roll bar are adopted as actuators that generate yaw and roll moments, respectively. The proposed method is shown to be effective in preventing rollover through the simulations on nonlinear multi-body dynamic simulation software, CarSim.

• Journal of Auto-vehicle Safety Association
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• v.5 no.1
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• pp.56-61
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• 2013

This paper presents a development of the Advanced Emergency Braking (AEB) Algorithm for passenger vehicles. The AEB is the system to slow the vehicle and mitigate the severity of an impact when a rear end collision probability is increased. To mitigate a rear end collision, the AEB comprises of a millimeter wave radar sensor, CCD camera and vehicle parameters of which are processed to judge the likelihood of a collision occurring. The main controller of the AEB algorithm is composed of the two control stage: upper and lower level controller. By using the collected obstacle information, the upper level controller of the main controller decides the control mode based not only on parametric division, but also on physical collision capability. The lower level controller determines warning level and braking level to maintain the longitudinal safety. To decide the braking level, Last Ponit To Brake and Steer (LPTB/LPTS) are compared with current driving statues. To demonstrate the control performance of the proposed AEBS algorithm's, closed-loop simulation of the AEBS was conducted by using the Matlab simlink and CarSim software.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.17-22
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• 2019

This paper describes the tracking algorithm performance evaluation for autonomous vehicle using a safety envelope based path. As the level of autonomous vehicle technologies evolves along with the development of relevant supporting modules including sensors, more advanced methodologies for path generation and tracking are needed. A safety envelope zone, designated as the obstacle free regions between the roadway edges, would be introduced and refined for further application with more detailed specifications. In this paper, the performance of the path tracking algorithm based on the generated path would be evaluated under safety envelop environment. In this process, static obstacle map for safety envelope was created using Lidar based vehicle information such as current vehicle location, speed and yaw rate that were collected under various driving setups at Seoul National University roadways. A level of safety was evaluated through CarSim simulation based on paths generated with two different references: a safety envelope based path and a GPS data based one. A better performance was observed for tracking with the safety envelop based path than that with the GPS based one.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.1
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• pp.85-95
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• 2013

As the conventional hydraulic power steering system in the passenger vehicles is being rapidly replaced by EPS (Electric Power Steering) system, performance evaluation of the EPS system has become an important issue in the automotive industries. But the evaluation process takes significant expertise since steering conditions in the test protocols must be implemented with high accuracy. EPS HILS (Hardware-In the-Loop Simulation) system is developed together with robot steering system in this study. Main components of EPS HILS system include: C-EPS hardware, CarSim vehicle model, and road reaction force generation system powered by servo motor. The robot steering system, operated by another servo motor, was combined with EPS HILS system to substitute for steering efforts of human driver. The road reaction force generation system and the robot steering system were carefully validated by using the data obtained from vehicle tests. An on-center handling test was conducted by using EPS HILS system combined with the robot steering system. In the result of this study, robot-steered EPS HILS system developed with its high reliability and no need of skilled driver's, can be widely adopted to evaluate any performance of EPS system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.10
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• pp.1879-1885
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• 2017

This paper discusses the trajectory tracking system of unmanned ground vehicles based on predictive control. Because the unmanned ground vehicles can not satisfactorily complete the path tracking task, highly efficient and stable trajectory control system is necessary for unmanned ground vehicle to be realized intelligent and practical. According to the characteristics of unmanned vehicle, this paper built the kinematics tracking models firstly. Then studied algorithm solution with the tools of the optimal stability analysis method and proposed a tracking control method based on the model predictive control. The controller used a kinematics-based prediction model to calculate the predictive error. This controller helps the unmanned vehicle drive along the target trajectory quickly and accurately. The designed control strategy has the true robustness, simplicity as well as generality for kinematics model of the unmanned vehicle. Furthermore, the computer Simulink/Carsim results verified the validity of the proposed control method.