• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.6
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• pp.182-197
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• 1999

Described in this paper is an optimal driving control algorithm which focused on the improvement of fuel economy and the minimization of pollutant emissions in the parallel type hybrid drivertrain system for transit bus. For the energy balance among components such as engine, induction machine and buttery, the algorithm for power split ration determine is proposed. When it is implemented in the hybrid electric control unit(HECU) , using the sub-optimal method and the approximate technique , it is possible to save the memory , to shorten the calculation time, and to achieve the efficient driving actually. A Shift strategy for automated manual transmission is the other side of the driving control algorithm. It enables to select the optimal gear by using several shift maps which were predefined from the proposed method in this paper, As a results of driving simulation, it is proved that these algorithms make the hybrid drivetrain system to reduce fuel consumption and emissions considerably and to have the ability to the efficient use of battery.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.6-6
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• 2000

By using the information obtained from the outputs of MR(MagnetoResistive) sensors for an Unmanned Vehicle Driving System, we develop an algorithm that decides the distance and direction between vehicle and the guideline which is made by the magnet. To improve the robust tracking properties of the closed loop system, we introduce H$\infty$ controller and its application for the Unmanned Vehicle Driving System.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.3
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• pp.183-190
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• 2016

In this study, we conduct linear and nonlinear modeling of the DC motor driving system of a wheeled mobile robot, which is a nonlinear system involving dead zone, friction, and saturation. The DC motor driving system consists of a DC motor, a wheel, and gears. A linear DC motor driving system is modeled using a steady-state response and parameter measurements. A nonlinear DC motor driving model is identified with the use of the Hammerstein-Wiener method. By using these models, PID controllers for the DC motor system are then established. Each PID controller is applied as a low-level controller in order to achieve posture stabilization control for the real mobile robot. We also compare the performance of the proposed PID controllers in posture stabilization experiments by using several different final robot postures.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.293-298
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• 2005

In this paper, we introduced a simulator to visualize the driving scenery of newly developed train called the K-AGT(Korea Automated Guideway Transit). The simulator consists of mainly two parts; control system and display system. In the control system, user can control the driving speed of the K-AGT, the driving environment(day and night), the operation of the train door and the screen door and user's views(driver's view, left window view, right window view, passenger's view). In the display system, immersive driving scenery generated by stereoscopic head mount display system and 3 channel PDP display system are displayed. We are expect to utilize the system to share the idea among customer, designer and constructor and verify the operating condition of the K-AGT intuitively.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.7
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• pp.650-658
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• 2012

This paper proposes a high performance position controller for a driving system using a time optimal controller which has been widely used to control driving systems to achieve desired reference position or velocity in a minimum response time. The main purpose of this research lies in an improvement of transient response performance rather than that of steady-state response in comparison with other control strategies. In order to refine the scheme of time optimal control, Lyapunov stability proofs are incorporated in a controller of standard second order system model. This scheme is applied to the control of a driving system. In view of the simulation and experiment results, the standard second order system model exhibits better minimum-time control performance and robustness than double integral system model does.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.5
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• pp.115-121
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• 2001

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. Vehicle driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that vehicle-driving-load-adaptive control can provide an ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only the variation of driving load but also the modeling errors.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.653-658
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• 2000

A driving load estimation method for intelligent cruise control(ICC) vehicles has been proposed in this paper. The driving load is one of the most important factors of perturbations in vehicle control and can affect the control performance critically. The Effect of the control with driving load estimation on vehicle-to-vehicle distance control has been presented and investigated via computer simulations and vehicle tests. The results show that the control with driving load estimation can provide ICC system with a good acceleration tracking performance. In addition, the results show that driving load estimation can compensate not only variation of driving load but also the modeling errors.

• Transactions of the Korean Society of Automotive Engineers
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• v.7 no.7
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• pp.250-257
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• 1999

Driving simulators are used effectively for human factor study, vehicle system development and other purposes by enabling to reproduce actural driving conditions in a safe and tightly controlled enviornment. Interactive simulation requries appropriate sensory and stimulus cuing to the driver . Sensory and stimulus feedback can include visual , auditory, motion, and proprioceptive cues. A fixed-base driving simulator has been developed in this study for vehicle system developmnet and human factor study . The simulator consists of improved and synergistic subsystems (a real-time vehicle simulation system, a visual/audio system and a control force loading system) based on the motion -base simulator, KMU DS-Ⅰ developed for design and evaluation of a full-scale driving simulator and for driver-vehicle interaction.

• Journal of Auto-vehicle Safety Association
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• v.3 no.2
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• pp.28-33
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• 2011

This paper presents driving path estimation algorithm for adaptive cruise control system and advanced emergency braking system using multi-sensor fusion. Through data collection, yaw rate filtering based road curvature and vision sensor road curvature characteristics are analyzed. Yaw rate filtering based road curvature and vision sensor road curvature are fused into the one curvature by weighting factor which are considering characteristics of each curvature data. The proposed driving path estimation algorithm has been investigated via simulation performed on a vehicle package Carsim and Matlab/Simulink. It has been shown via simulation that the proposed driving path estimation algorithm improves primary target detection rate.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.608-613
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• 2002

In this paper we developed the MPC sensor for steering control and steering control of the AGVDS(Autonomous Guided Vehicle Driving System) for Durability test. Among durability tests, the accelerated durability test has been widely used to evaluate the durability of vehicle structure and chassis parts in a short period of time on the designed road that has severe surface conditions. However it increased the drivers fatigue mainly caused by the severe driving conditions. The driver's difficulty to maintain the constant speed and control the steering wheel reduces the reliability of test results. In addition to the general detecting sensor for steering control was restricted by surrounding condition. So we need to develop steering control sensor was robust in the bad driving condition. In this paper we developed steering control sensor using magnetic induction which is robust in the bad driving condition and implemented the AGVDS.