• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.635-641
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• 2016

In order to drive a hybrid propulsion device which combines an engine and an electric propulsion unit, battery packs that contain dozens of unit cells consisting of a lithium-based battery are used to maintain the power source. Therefore, it is necessary to more strictly manage a number of battery cells at any given time. In order to manage battery cells, generally voltage, current, and temperature data under load condition are monitored from a personal computer. Other important elements required to analyze the condition of the battery are the internal resistances that are used to judge its state-of-health (SOH) and the open-circuit voltage (OCV) that is used to check the battery charging state. However, in principle, the internal resistances cannot be measured during operation because the parallel equivalent circuit is composed of internal loss resistances and capacitance. In most energy storage systems, battery management system (BMS) operations are carried out by using data such as voltage, current, and temperature. However, during operation, in the case of unexpected battery cell failure, the output voltage of the power supply can be changed and propulsion of the hybrid vehicle and vessel can be difficult. This paper covers the implementation of a high safety battery management system (HSBMS) that can estimate the OCV while the device is being driven. If a battery cell fails unexpectedly, a DC power supply with lithium iron phosphate can keep providing the load with a constant output voltage using the remainder of the batteries, and it is also possible to estimate the internal resistance.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.335-336
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• 2016

This paper introduces a bidirectional full-bridge converter with new active damp structure. The proposed active damp circuit can damp the oscillating voltage across the rectifier diodes with a smaller voltage stress of the damping capacitor and eliminate the circulating current. In addition, the proposed converter can achieve additional advantages such as nearly ZCS switching for leading-leg switches and no recovery current for rectifier-bridge by the suitable design of the damp capacitor to resonate with leakage inductor. Since the ZVS is achieved for both leading-leg and lagging-leg switches by the magnetizing current of the transformer, it can be achieved regardless of the load variation. A 3.3 kW prototype converter is implemented for vehicle-to-grid (V2G) application and the advantages of the proposed converter are verified by the experiments. The maximum efficiencies of 98.2% and 97.6% have been achieved for the buck mode and boost mode operation, respectively.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.12
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• pp.689-697
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• 2005

In this paper, an application of a decentralized $H_{\infty}$ controller(DHC) to multiple controlled-permanent magnet(CMAG) magnetic levitation(Maglev) systems is presented. The designed DHC using two Riccati equations iteratively has simpler structure and needs less computational loads than conventional centralized $H_{\infty}$ controller. A target plant is a hybrid-type CMAG system with permanent magnet and coil, and its mathematical model is firstly derived to design the DHC. To implement the designed algorithm, a real Maglev vehicle system including digital controller, chopper, sensor, etc., is manufactured. To compare the performances of the DHC method with an observer-based state feedback control(OSFC), the input tracking and disturbance rejection characteristics are experimentally tested. As performance indices(PI), integral of squared error(ISE), integral of absolute error(IAE), integral of time multiplied by absolute error(ITAE) and integral of time multiplied by squared error(ITSE) are used. From the experimental results, it can be seen that the input tracking and disturbance rejection performances of the DHC are better than those of the conventional controller.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.12
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• pp.567-572
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• 2002

In these days, diesel vehicle or power plant emits $NO_X\; and SO_2$ which cause air pollution like acid-rain, ozone layer destroy and optical smoke, therefore there are many kinds of methods considered for removing them such as SCR, catalyst, plasma process, and plasma-catalyst hybrid process. T$TiO_2$ is commonly used as catalyst to remove $NO_X$ gas because it have very excellent chemical characteristic as photo catalyst. In this paper, $NO_X$ sensing characteristic of $TiO_2$ thin film deposited by R.F Magnetron sputtering is investigated. A finger shaped electrode on $Al_2$O$_3$ substrate is designed and $TiO_2$ is deposited on the electrode by the magnetron sputtering deposition system. Chemical composition of the deposited $TiO_2$ thin film is $TiO_{1.9}$ by RBS analysis. When the UV is irradiated on it with flowing air, capacitance of $TiO_2$ thin film increases, however, when NO gas is put into the system with air, it immediately decreases because of photo chemical reaction. and it monotonously decreases with increasing NO concentration.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2006.05a
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• pp.309-314
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes maximum torque control of IPMSM drive using adaptive learning fuzzy neural network and artificial neural network. This control method is applicable over the entire speed range which considered the limits of the inverter's current md voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_d$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using adaptive teaming fuzzy neural network and artificial neural network. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper proposes speed control of IPMSM using adaptive teaming fuzzy neural network and estimation of speed using artificial neural network. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled adaptive teaming fuzzy neural network and artificial neural network, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper proposes the analysis results to verify the effectiveness of the adaptive teaming fuzzy neural network and artificial neural network.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1433-1444
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• 2017

A family of non-isolated DC-DC three-port converters (TPCs) that allows for a more flexible power flow among a renewable energy source, an energy storage device and a current-reversible DC bus is introduced. Most of the reported non-isolated topologies in this area consider only a power consuming load. However, for applications such as hybrid-electric vehicle braking systems and DC microgrids, the load power generating capability should also be considered. The proposed three-port family consists of one unidirectional port and two bi-directional ports. Hence, they are well-suited for photovoltaic (PV)-battery-DC bus systems from the power flow viewpoint. Three-port converters are derived by combining different commonly known power converters in an integrated manner while considering the voltage polarity, voltage levels among the ports and the overall voltage conversion ratio. The derived converter topologies are able to allow for seven different modes of operation among the sources and load. A three-port converter which integrates a boost converter with a buck converter is used as a design example. Extensions of these topologies by combining the soft-switching technique with the proposed design example are also presented. Experiment results are given to verify the proposed three-port converter family and its analysis.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.07b
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• pp.1184-1187
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• 2003

Electrochemical capacitors are becoming attractive energy storage systems particularly for applications involving high power requirements such as hybrid systems consisting of batteries and electrochemical capacitors for electric vehicle propulsion. A new type electric double layer capacitor (EDLC) was constructed by using carbon nanofibers (CNFs) and DAAQ(1,5-diaminoanthraquinone) electrode. Carbonaceous materials are found in variety forms such as graphite, diamond, carbon fibers etc. While all the carbon nanofibers include impurities such as amorphous carbon, nanoparticles, catalytic metals and incompletely grown carbons. We have eliminated of Ni particles and some carbonaceous particles in nitric acid. Nitric acid treated CNFs could be covered with very thin DAAQ oligomer from the results of CV and TG analyses and SEM images. DAAQ oligomer film exhibited a specific capacity as 45-50 Ah/kg in 4M $H_2SO_4$. We established Process Parameters of the technique for the formation of nano-structured materials. Furthermore, improved the capacitive properties of the nano structured CNFs electrodes using controlled solution chemistry. As a result, CNFs coated by DAAQ composite electrode showed relatively good electrochemical behaviors in acidic electrolyte system with respect to specific capacity and scan rate dependency.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.3
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• pp.3-9
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• 2017

Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.12
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• pp.1097-1107
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• 2015

General VTOL aircraft uses gas turbine engine which has high power to weight ratio. However, in the VTOL UAV in small sector, the gas turbine as a prime mover is not adequate because of the limitation of the high fuel consumption ratio of the gas turbine. In this research, The Series Hybrid-Electric Propulsion System(SHEPS) has been proposed and technology survey & comparison analysis has conducted to constitute propulsion system for engine, electric motor and battery. To achieve this object a 65kg-class P-UAV from "Company I" was used. And to estimate the validity of power control algorithm and developed power management control, Matlab/simulink$^{(R)}$ has been used for the simulation. As a result, the developed algorithm worked comparatively well and the research has predicted that SHEPS was satisfied enough for 7 hour of endurance for mission profile.