• Journal of IKEEE
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• v.18 no.2
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• pp.282-290
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• 2014

This paper presents the design of embedded electrical power control unit for Personal Electrical Vehicle(PEV). The embedded unit is designed using PIC18F8720 processor, 16Mb flash ROM, 32Mb SDRAM and signal condition circuits. The proposed PEV consists of 4KW in-wheel Brushless DC Motor(BLDCM), 3 phase voltage source inverter with the $180^{\circ}$ conduction space vector PWM method, PID speed controller and the embedded control unit. The PEV has mechanical manufacture of inverse 3 wheel system, which is applied by the in-wheel BLDCM and steering mechanism with tilting function. Also, the performances of the proposed embedded electrical power control unit are verified through the lab experiment and road driving test of PEV.

• Journal of IKEEE
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• v.25 no.1
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• pp.148-155
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• 2021

As robot technology advances, research on the driving system of mobile robots is actively being conducted. The driving system of a mobile robot configured based on two-wheels and four-wheels has an advantage in unidirectional driving such as a straight line, but has disadvantages in turning direction and rotating in place. A ball robot using a ball as a wheel has an advantage in omnidirectional movement, but due to its structurally unstable characteristics, balancing control to maintain attitude and driving control for movement are required. By estimating the position from an encoder attached to the motor, conventional ball robots have a limitation, which causes the accumulation of errors during driving control. In this study, a driving control system was proposed that estimates the position coordinates of a ball robot through image processing and uses it for driving control. A driving control system including an image processing unit, a communication unit, a display unit, and a control unit for estimating the position of the ball robot was designed and manufactured. Through the driving control experiment applying the driving control system of the ball robot, it was confirmed that the ball robot was controlled within the error range of ±50.3mm in the x-axis direction and ±53.9mm in the y-axis direction without accumulating errors.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.3
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• pp.267-274
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• 2014

The purpose of this study is to identify a relationship between the time taken and the characteristics of touch key for touch-screen-based in-vehicle information system (IVIS) and to suggest a new Fitts' law formula that is added a driving speed parameter. Many studies already have shown that Fitts' law is well fitted in various devices for primary tasks, but there is no study of Fitts' law for secondary task in dual-task situation. Fitts' law may not be applied to the secondary task as it is, because the secondary task performance can be affected by the amount of attention for the primary task. To verify this, we carried out an experiment that showed whether pointing task to touch-screen-based IVIS during driving is affected by driving speeds or not. In the experiment, 30 people were volunteered for participants and the participants carried out driving task and pointing task on the screen of IVIS simultaneously. We measured the time to point a touch key on IVIS for every condition (3 driving speeds${\times}5$ touch key sizes${\times}7$ distances between steering wheel and touch key). As a result, there was an effect of driving speed on the pointing time. As we extended the index of difficulty of the conventional Fitts' law formula by incorporating driving speed, we established an extended Fitts' law formula for pointing on IVIS, which showed better accordance with dual task situation. This study can be evidence that secondary task performance is affected by degree of concentration on primary task, and the extended Fitts' law formula can be useful to design interfaces of IVIS.

• 전자공학회논문지 IE
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• v.49 no.2
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• pp.30-39
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• 2012

An effective drowsy driver detection system is needed, because the probability of accident is high for drowsy driving and its severity is high at the time of accident. However, the drowsy driver detection system that uses bio-signals or vision is difficult to be utilized due to high cost. Thus, this paper proposes a drowsy driver detection algorithm by using steering angle sensor, which is attached to the most of vehicles at no additional cost, and vehicle information such as brake switch, throttle position signal, and vehicle speed. The proposed algorithm is based on jerk criterion, which is one of drowsy driver's steering patterns. In this paper, threshold value of each variable is presented and the proposed algorithm is evaluated by using acquired vehicle data from hardware in the loop simulation (HILS) through CAN communication and MATLAB program.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.2
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• pp.79-85
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• 2007

The skid-steering method that applied a number of mobile robot currently is very effective in narrow area. But it contains several problems of its natural properties, slip, occurred by different direction between vehicle's driving and wheel's rotary. From this thesis we want to suggest suitable structure of $6{\times}6$ skid steering wheeled vehicle and method of driving by analyzing the behavior of $6{\times}6$ skid-steered wheeled vehicle by engineering analytical method

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.642-651
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• 2016

For the acceleration and brake systems of an autonomous vehicle, the dynamic models from acceleration (brake) pedal input to driving(braking) torque at the vehicle wheel are represented by a set of linear transfer functions in this paper. We present an experimental method that can identify these models using a single rectangular pulse response data. Various magnitude of inputs with different running speeds are applied to experimental tests. All the identified models are demonstrated by the measured data. Both acceleration and brake models have been also validated by comparing the velocity of a full vehicle model associated with the proposed models with the measured vehicle velocity.

• Journal of Industrial Technology
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• v.19
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• pp.31-42
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• 1999

This paper presents a method for evaluating the performance of a leaf spring suspension and an air spring suspension systems for trucks in terms of ride and handling. Leaf springs, which generally have non-linear progressive force-deflection characteristics, are modeled using beam and contact elements. The leaf spring analysis model shows good correlation with experimental results. Each component of an air spring suspension system, which is a single leaf, air spring, height control valve, compressor and linkages, is modeled appropriately. Non-linear characteristics of air spring are accounted for using the measured data, and pressure and volume relations for height control system is also considered. The wheel rate of the air suspension is taken lower but roll stiffness is taken higher than those of leaf springs to improve ride and handling performance, which is verified through driving simulations.

• Journal of IKEEE
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• v.23 no.3
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• pp.844-851
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• 2019

As wearable technology is becoming more common and a part of our lives, there have been many efforts to offer various smart services with wearable devices, such as motion recognition, safety of driving, and so on. In this paper, we present a method that exploits the 9-axis inertial sensors embedded in a smartwatch to identify whether the user is a vehicle driver or not and to estimate the steering wheel turning direction in the vehicle. The system consists of three components: (i) position recognition, (ii) driver recognition, and (iii) steering-wheel turning detection components. We have developed a prototype system for detecting user's motion with Arduino boards and IMU sensors. Our experiments show high accuracy in recognizing the driver and in estimating the wheel rotation angle. The average experimental error was $11.77^{\circ}$ which is small enough to perceiver the turning direction of steering-wheel.

• Journal of the Ergonomics Society of Korea
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• v.31 no.5
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• pp.637-646
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• 2012

Objective: The aim of this study was to develop the adaptive device for severe physical disabilities using smart device in the driving simulator and its performance evaluation. Development of appropriate driving adaptive device for the people with serious physical limitation could contribute to maintain their community mobility. Background: There is lack of adaptive driving devices for the people with disabilities in Korea. However, if smart device systems like iPod and iPhone are used for driving a car, the people with serious physical limitations can improve their community mobility. Method: Both gyroscope and accelerometer from iPod were used to measure the tilted angle of the smart device for driving. Customized Labview program was also used to control three axis motors for steering wheel, accelerator and brake pedals. Thirteen subjects were involved in the experiment for performance evaluation of smart device in simulator. Five subjects had driver licenses. Another four subjects did not have driver licenses. Others were people with disabilities. Results: Average driving score of the normal group with driver license in the simulator increased 46.6% compared with the normal group without driver license and increased 30.4% compared with the disabled group(p<0.01). There was no significant difference in the average driving score between normal group without driver license and disabled group(p>0.05). Conclusion: The normal group with driver license showed significantly higher driving score than other groups. The normal group without driver license and disabled group could improve their driving skills with training in simulator. Application: If follow-up studies would be continued and applied in adapted vehicle for on road environment, many people with more severe disabilities could drive and improve the quality of life.

• Journal of Electrical Engineering and Technology
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• v.4 no.4
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• pp.499-509
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• 2009

Electric vehicles (EV) are developing fast during this decade due to drastic issues on the protection of environment and the shortage of energy sources, so new technologies allow the development of electric vehicles (EV) by means of electric motors associated with static converters. The proposed propulsion system consists of two induction motors (IM) that ensure the drive of the two back driving wheels. 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. This paper presents the study of an hybrid Fuzzy-sliding mode control (SMC) strategy for the electric vehicle driving wheels, stability improvement, in which the fuzzy logic system replace the discontinuous control action of the classical SMC law. Our electric vehicle fuzzy-sliding mode control's simulated in Matlab SIMULINK environment, the results obtained present the efficiency of the proposed control with no overshoot, the rising time is perfected with good disturbances rejections comparing with the classical control law.