• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.860-868
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• 2016

A bidirectional DC-DC converter (BDC) is an indispensable electrical unit for the electric vehicles (EVs). High efficiency, high power density, isolation, light weight and reliability are all essential requirements for BDC. In this paper, a 3 kW BDC for the battery charger of EVs is proposed. The proposed converter consists of a half-bridge structure on the primary side and an isolation transformer and a synchronous rectifier structure on the secondary side. With this topology, minimum number of switching devices are required for bidirectional power flow between the two dc buses of EVs. The easy implementation of the synchronous rectification gives advantages in terms of efficiency, cost and flexibility. The proposed BDC achieves high efficiency when operating in both modes (step-up and step-down). A 3 kW prototype is implemented to verify theoretical analysis and the performance of the proposed converter.

• The Journal of Industrial Distribution & Business
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• v.9 no.3
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• pp.57-68
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• 2018

Purpose - The purpose of this study is to classify that the quality factors for comparing the Visegrard Group with the Nordic Council have historical similarities against Germany and the Soviet Union. However, this is because in the integrated European market, the competitiveness possessed by the two groups of countries is invested in the priority order to grow. Research design, data, and methodology - The study was conducted on the research design, and the reason for trying to compare the competence of the automobile industry in the assessment of industrial capability is that the Visegrard Group focuses on automotive production and the Nordic Association focuses on the commercialization of the automobile(market). In this study, searching and quantifying indirect evidence was made through standards are more complementary in Europe since each country acts like the role of the European automotive industry for example, which is different from the realistic evaluation criteria, are more important than those of the United States(first in the world) or Germany(first in Europe). Results - The results of this study are as follows: In the global EV market U.S.(export: $ 2.62 billion /share: 36.7%), Germany($ 1.29 billion /18.1%), France($ 390 million /5.4%), United Kingdom($ 380 million /5.4%), and South Korea($ 320 million/ 4.4%). South Korea's share of the EV market is 4.4%, while TSI reaches at +0.9 which measures the comparative advantage of a specific commodity in the world trade market. There is great potential for evaluated as products processing in export competition. But, commercialization, standardization, and overall market expansion did not have a positive impact on global satisfaction. Conclusions - EVs put importance on various utilities. So this suggests that Korea's exports to the EU, including the Visegrard Group, should be more focused on marketability when illuminating with a sharing industrial system under the European Union. It is necessary to specialize in manufacturing and commercialization by country(region) to prepare sharing economy and blockchain in order to create a smart-sharing city linked on artificial intelligence, as the commercialization of electric vehicles, which will have a larger growth rate than that of manufacturing in the fourth revolutionary era.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.2
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• pp.228-231
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• 2015

In power system research fields, one of current key issues is the construction and commercialization of micro grid site which is called green island, carbon zero island, energy independent island, building micro grid, etc. and various affiliated technologies have been being vigorously developed to realize. In addition, various researches about electric vehicles (EVs) are in progress and it is expected to penetrate rapidly with the next a few years. Some new load models should be developed integrating with electric vehicle loads because the EVs' deployment could cause the change of load composition rate on power system planning and operations. EVs are also resources for micro grid as well as distributed generation and demand response so that various supply and demand side resources should be considered for micro grid researches. In this paper, the load composition rate of residential sectors is prospected considering the deployment of EVs and the resource configuration of micro grid is optimized based on net present cost. In the optimization, the load patten of case studies includes EV's charging characteristics and various cases are simulated comparing micro grid environment and normal condition. HOMER is used to compare various cases and economic effects.

• International Journal of Advanced Culture Technology
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• v.3 no.1
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• pp.90-100
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• 2015

Green technologies such as renewable energy resources, Electric Vehicles and Plug-in Hybrid Electric Vehicles (EVs/PHEVs), electric locomotives, etc. are continually increasing at the existing power network especially distribution levels, which are Medium Voltage (MV) and Low Voltage (LV). It can be noted that the increasing level of green technologies is driven by the reduction emission policies of carbon dioxide ($CO_2$). The green technologies can affect the quality of power, and hence its impacts of are analysed. In practical, the environment such as wind, solar irradiation, temperature etc. are uncontrollable, and therefore the output power of renewable energy in that area can be varied. Moreover, the technology of the EVs/PHEVs is still developed in order to improve the performance of supply and driving systems. This means that these developed can cause harmonic distortion as the control system is mostly used power electronics. Therefore, this paper aims to analyse the voltage variation and harmonic distortion in distribution power network in urban area in Europe due to the combination between wind turbine, hydro turbine, photovoltaic (PV) system and EVs/PHEVs. More realistic penetration levels of SSDGs and EVs/PHEVs as forecasted for 2020 is used to analyse. The dynamic load demands are also taken into account. In order to ensure the accurate of simulation results, the practical parameters of distribution system are used and the international standards such as Institute of Electrical and Electronics Engineers (IEEE) standards are also complied. The suggestion solutions are also presented. The MATLAB/Simulink software is chosen as it can support complicate modelling and analysis.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.451-458
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• 2017

An Electric Vehicle (EV) is operated with the electric energy of a battery in place of conventional fossil fuels. Thus, a suitable charging infrastructure must be provided to expand the use of electric vehicles. Because the battery of an EV must be charged to operate the EV, expanding the number of EVs will have a significant influence on the power supply and demand. Therefore, to maintain the balance of power supply and demand, it is important to be able to predict the numbers of charging EVs and monitor the events that occur in the distribution system. In this paper, we predict the hourly charging rate of electric vehicles using transformation matrix, which can describe all behaviors such as resting, charging, and driving of the EVs. Simulation with transformation matrix in a specific region provides statistical results using the Monte-Carlo Method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1793-1799
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• 2016

As one of the main trends in global industries is eco-friendly energy, the interest on Electric Vehicle(EV) has been increased. However, if large amount of EVs start to charging, it could cause rapid increase in demand power of the power system. To guarantee stable operation of the power system, those unpredictable power consume should be mitigated. In this paper, therefore, we propose a practical smart EVs charging scheme to prevent the rapid increase of the demand power and also provide load flattening function. For that we considered Time-of-Use(ToU) price and actual data such as driving pattern and parameters of distribution system. Simulation results show that the proposed method provides proper load flattening function while preventing the rapid increase of the demand power of the power system.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2220-2226
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• 2018

Electric vehicles (EVs) are significant resources for demand response (DR). Thus, it is essential for EV aggregators to quantitatively evaluate their capability for DR. In this paper, a concept of dynamic equivalent battery (DEB) is proposed as a metric for evaluating the DR performance using EVs. The DEB is the available virtual battery for DR. The capacity of DEB is determined from stochastic calculation while satisfying the charging requirements of each EV, and it varies also with time. Further, a new indicator based on the DEB and time-varying electricity prices, named as value of DEB (VoDEB), is introduced to quantify the value of DEB coupled with the electricity prices. The effectiveness of the DEB and the VoDEB as metrics for the DR performance of EVs is verified with the simulations, where the difference of charging cost reduction between direct charging and optimized bidding methods is used to express the DR performance. The simulation results show that the proposed metrics accord well with the DR performance of an EV fleet. Thus, an EV aggregator may utilize the proposed concepts of DEB and VoDEB for designing an incentive scheme to EV users, who participate in a DR program.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.6
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• pp.783-790
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• 2012

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4988-5012
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• 2019

As a subset of the Internet of Things, the Internet of Energy (IoE) is expected to tackle the problems faced by the current smart grid framework. Notably, the conventional day-ahead power scheduling of the smart grid should be redesigned in the IoE architecture to take into consideration the intermittence of scattered renewable generations, large amounts of power consumption data, and the uncertainty of the arrival time of electric vehicles (EVs). Accordingly, a day-ahead power scheduling system for the future IoE is proposed in this research to maximize the usage of distributed renewables and reduce carbon emission caused by the traditional power generation. Meanwhile, flexible charging mechanism of EVs is employed to provide preferred charging options for moving EVs and flatten the load profile simultaneously. The simulation results revealed that the proposed power scheduling mechanism not only achieves emission reduction and balances power load and supply effectively, but also fits each individual EV user's preference.

• Journal of Electrical Engineering and Technology
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• v.13 no.5
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• pp.1927-1934
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• 2018

In this paper, we studied the state of charge (SOC) estimation algorithm of a high-capacity lithium secondary battery for electric vehicles (EVs) considering temperature characteristics. Nonlinear characteristics of high-capacity lithium secondary batteries are represented by differential equations in the mathematical form and expressed by the state space equation through battery modeling to extract the characteristic parameters of the lithium secondary battery. Charging and discharging equipment were used to perform characteristic tests for the extraction of parameters of lithium secondary batteries at various temperatures. An extended Kalman filter (EKF) algorithm, a state observer, was used to estimate the state of the battery. The battery capacity and internal resistance of the high-capacity lithium secondary battery were investigated through battery modeling. The proposed modeling was applied to the battery pack for EVs to estimate the state of the battery. We confirmed the feasibility of the proposed study by comparing the estimated SOC values and the SOC values from the experiment. The proposed method using the EKF is expected to be highly applicable in estimating the state of the high-capacity rechargeable lithium battery pack for electric vehicles.