• The Transactions of the Korean Institute of Power Electronics
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• v.22 no.2
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• pp.175-180
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• 2017

The measurement of three-phase current is important to control the instantaneous torque of a interior permanent magnet synchronous motor(IPMSM) using a three-phase inverter. Therefore, shunt resistors are used in low-cost motor-driving systems to measure three-phase current instead of additional current sensors that are too expensive for these systems. However, in certain regions of a space vector plane, shunt resistors cannot reconstruct three-phase current in high-speed driving mode. In this paper, predictive current control is used to compensate for the three-phase current in those regions, which results in a reduction of current ripple in a three-shunt sensing inverter(TSSI) and torque ripple in IPMSM.

• Journal of ILASS-Korea
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• v.21 no.3
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• pp.155-161
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• 2016

Injected fuel pressure waves of a common rail injector with various current profiles supplied to the injecor were measured using Bosch method. In order to drive the common rail injector, the current in the solenoid should be controlled using what is known as a peak and hold pattern, which consists of a high current level with a short time duration (peak) in the first step and a low current level with a long time duration (hold) in the subsequent step. The current profile can be shaped by swithcing an injector driving power source with the peak and hold waves. The capture, compare and PWM (CCP) pin in the microprocessor was used to generate the combined peak and hold waves. The PWM square wave generated from the CCP pin has a duty ratio of 100% for the peak current and 10% or 30% for the hold pattern. Five patterns of the current profile were generated by combining the peak and hold wave. The common rail pressure is controlled at 75, 100, and 130 MPa. As the fuel rail pressure increases, the variations of the measured fuel injection pressure wave according to the current profiles decrease.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.346-348
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• 2005

In this paper, we designed a vehicle active suspension controller. Vehicle suspensions have various design objects with tradeoff among them and these objects cannot be satisfied under all driving conditions. We need to design a controller adapted to variable driving conditions changing the objects of vehicle suspensions. To design such a controller, we must be able to detect the current driving conditions and focus on the road frequencies giving us useful and important information about driving conditions. Detecting the road frequencies, we use the Fourier Transform. A unexpected driving change like a speed bump was also included to items the new designed controller must consider.

• Journal of Power Electronics
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• v.19 no.2
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• pp.403-412
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• 2019

Aiming at the problems of large dv/dt and di/dt in traditional single-ended converters and high electromagnetic interference (EMI) noise levels, a single-ended isolated converter using the secondary resonance technique is proposed in this paper. In the proposed converter, the voltage stress of the main power switch can be reduced and the voltage across the output diode is clamped to the output voltage when compared to the conventional flyback converter. In addition, the peak current stress through the main power switch can be decreased and zero current switching (ZCS) of the output diode can be achieved through the resonance technique. Moreover, the EMI noise coupling path and an equivalent model of the proposed converter topology are presented through the operational principle of the proposed converter. Analysis results indicate that the common mode (CM) EMI noise and the differential mode (DM) EMI noise of such a converter are deduced since the frequency spectra of the equivalent controlled voltage sources and controlled current source are decreased when compared with the traditional flyback converter. Furthermore, appropriate parameter selection of the resonant circuit network can increase the equivalent impedance in the EMI coupling path in the low frequency range, which further reduces the common mode interference. Finally, a simulation model and a 60W experimental prototype of the proposed converter are built and tested. Experimental results verify the theoretical analysis.

• Korean Journal of Materials Research
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• v.31 no.10
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• pp.586-591
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• 2021

This paper proposes a mathematical model that can calculate the luminescence characteristics driven by alternating current (AC) power using the current-voltage-luminance (I-V-L) properties of organic light emitting devices (OLED) driven by direct current power. Fluorescent OLEDs are manufactured to verify the model, and I-V-L characteristics driven by DC and AC are measured. The current efficiency of DC driven OLED can be divided into three sections. Region 1 is a section where the recombination efficiency increases as the carrier reaches the emission layer in proportion to the increase of the DC voltage. Region 2 is a section in which the maximum luminous efficiency is stably maintained. Region 3 is a section where the luminous efficiency decreases due to excess carriers. Therefore, the fitting equation is derived by dividing the current density and luminance of the DC driven OLED into three regions, and the current density and luminance of the AC driven OLED are calculated from the fitting equation. As a result, the measured and calculated values of the AC driving I-V-L characteristics show deviations of 4.7% for current density, 2.9 % for luminance, and 1.9 % for luminous efficiency.

• Journal of Internet Computing and Services
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• v.24 no.1
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• pp.39-47
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• 2023

The development of autonomous driving and Advanced Driver Assistance System (ADAS) technology has grown rapidly in recent years. As most traffic accidents occur due to human error, self-driving vehicles can drastically reduce the number of accidents and crashes that occur on the roads today. Obviously, technical advancements in autonomous driving can lead to improved public driving safety. However, due to the current limitations in technology and lack of public trust in self-driving cars (and drones), the actual use of Autonomous Vehicles (AVs) is still significantly low. According to prior studies, people's acceptance of an AV is mainly determined by trust. It is proven that people still feel much more comfortable in personalized ADAS, designed with the way people drive. Based on such needs, a new attempt for a customized ADAS considering each driver's driving style is proposed in this paper. Each driver's behavior is divided into two categories: assertive and defensive. In this paper, a novel customized ADAS algorithm with high classification accuracy is designed, which divides each driver based on their driving style. Each driver's driving data is collected and simulated using CARLA, which is an open-source autonomous driving simulator. In addition, Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) machine learning algorithms are used to optimize the ADAS parameters. The proposed scheme results in a high classification accuracy of time series driving data. Furthermore, among the vast amount of CARLA-based feature data extracted from the drivers, distinguishable driving features are collected selectively using Support Vector Machine (SVM) technology by comparing the amount of influence on the classification of the two categories. Therefore, by extracting distinguishable features and eliminating outliers using SVM, the classification accuracy is significantly improved. Based on this classification, the ADAS sensors can be made more sensitive for the case of assertive drivers, enabling more advanced driving safety support. The proposed technology of this paper is especially important because currently, the state-of-the-art level of autonomous driving is at level 3 (based on the SAE International driving automation standards), which requires advanced functions that can assist drivers using ADAS technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.4
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• pp.1777-1783
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• 2012

In this paper, a new motor driving circuit is designed to improve the output performance of DC motor, and a controller is developed with the designed circuit. By the designed driving circuit, a controller can continuously drive DC motors by a transformer which has switching signals of a self-generated circuit to operate it. And while the DC motor have a maximum velocity, the reference voltage can be maintained higher value than that of triangle voltage and it makes the DC motor driving transistor ON and maximum power. A 24V-500W DC motor controller is developed with the proposed motor driving circuit, and also a small electric car is made and the driving test of it is executed. The test results shows that it can continuously control go and back speed of motor with 12A driving current. And also, it is verified that the over current and heat detecting function is operating correctly and the rest value of the used battery can be displayed as 6 step from 20 to 100%.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5842-5861
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• 2019

A current autonomous vehicle determines its driving strategy by considering only external factors (Pedestrians, road conditions, etc.) without considering the interior condition of the vehicle. To solve the problem, this paper proposes "An Optimal Driving Support Strategy(ODSS) based on an Genetic Algorithm for Autonomous Vehicles" which determines the optimal strategy of an autonomous vehicle by analyzing not only the external factors, but also the internal factors of the vehicle(consumable conditions, RPM levels etc.). The proposed ODSS consists of 4 modules. The first module is a Data Communication Module (DCM) which converts CAN, FlexRay, and HSCAN messages of vehicles into WAVE messages and sends the converted messages to the Cloud and receives the analyzed result from the Cloud using V2X. The second module is a Data Management Module (DMM) that classifies the converted WAVE messages and stores the classified messages in a road state table, a sensor message table, and a vehicle state table. The third module is a Data Analysis Module (DAM) which learns a genetic algorithm using sensor data from vehicles stored in the cloud and determines the optimal driving strategy of an autonomous vehicle. The fourth module is a Data Visualization Module (DVM) which displays the optimal driving strategy and the current driving conditions on a vehicle monitor. This paper compared the DCM with existing vehicle gateways and the DAM with the MLP and RF neural network models to validate the ODSS. In the experiment, the DCM improved a loss rate approximately by 5%, compared with existing vehicle gateways. In addition, because the DAM improved computation time by 40% and 20% separately, compared with the MLP and RF, it determined RPM, speed, steering angle and lane changes faster than them.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.5
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• pp.386-392
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• 2020

In this study, the drift current characteristics of charged particles are analyzed for panels fabricated by varying the waveform biasing of the active particle loading method (APLM), which is a method driven by the electrophoretic principle of loading charged particles into a cell of a barrier rib-type electronic paper. We prepare 3 panels using APLM and 1 panel without APLM. The waveform of APLM uses square wave and ramp wave, and the step voltage wave is applied to the driving voltage. The drift currents measured from the square wave and ramp wave with the same period applied by APLM are 4.872 µC and 5.464 µC, respectively, and the ramp wave is shown to be relatively advantageous for loading charged particles that have a large q/m. The time-current curve results confirm that the abrupt movement of charged particles is occurring. When the step form wave signal with a short time of 1s is first applied, initial large movement of the charged particles is confirmed to occur in all samples, which is understood as the effect of applying the voltage necessary to remove the imaging force. The results of this study are expected to improve the loading of charged particles into the electronic paper cell, driven by the electrophoretic principle and optimization of the driving conditions.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.38 no.2
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• pp.38-49
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• 2001

This paper presents a new voltage down converter(VDC) using charge and discharge current adjustment circuitry that provides high frequency application. This VDC consist of a common driving circuit and compensation circuits: 2 sensors and each driving transistors for controlling gate current of driving transistor. These sensors are operated as adaptive biasing method with high speed and low power consumption. This circuit is designed with a $0.62{\mu}m$ N well CMOS technology. In H-spice simulation results, internal voltage is bounded ( IV, +0.6V) in proposed circuitry when load current rapidly increases and decreases during Gns between 0 and $200m{\Lambda}$. And the recovery time of internal voltage is about 7ns and 10ns when load current increases and decreases respectively. That is fast better than common driving circuit. Total power consumption is about 1.2mW.