• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.131-138
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• 2023

Globally, the eco-friendly industry is developing due to the climate crisis. Electric vehicles are an eco-friendly industry that is attracting attention as it is expected to reduce carbon emissions by 30~70% or more compared to internal combustion engine vehicles. As electric vehicles become more popular, charging stations have become an important factor for purchasing electric vehicles. Recent research is using artificial intelligence to identify local demand for charging stations and select locations that can maximize economic impact. In this study, in order to contribute to the improvement of the performance of the electric vehicle charging station demand prediction model, nationwide data that can be used in the artificial intelligence model was defined and a pre-processing technique was proposed. In addition, a preprocessor, artificial intelligence model, and service web were implemented for real charging station demand prediction, and the value of data as a location selection factor was verified.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.3
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• pp.541-548
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• 2012

On this paper, we proposed a design rule of charger monitoring system which allow us to watch the charging status and verify it for building the electric chargers infrastructure by spread of electric vehicle. Gathering the charging status of battery by proposed system makes us to enhance the charging algorithm, to interface with BMS(Battery Management System) of electric vehicle, to control the charging process with users. Because the technology of rapid charging is dependant upon various factors such as a performance and stability of battery. We proposed the monitoring system of rapid charger based on CAN protocol that can watch a working status of rapid charger including the charging status of battery with real time and can reduce the charging time of battery with optimized status. We also implement it and evaluate its performance.

• Journal of the Korean Society for Precision Engineering
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• v.33 no.12
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• pp.1015-1020
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• 2016

An advantage of electric vehicles is that they are environmentally sustainable because they do not emit exhaust gases, such as $CO_2$ or Nox. A disadvantage is the low power performance of the motor and battery source, necessitating a reduction in the weight of the vehicle to increase efficiency. Another disadvantage is that the rechargeable battery enables an electric vehicle to only run for a limited number of miles before requiring electric charging. To solve these problems, the hybrid vehicle has been developed by combining environmental sustainability with the high performance of a conventional internal combustion engine. In this study, an electric UTV (Utility Terrain Vehicle) was transformed into a hybrid vehicle system by outfitting the vehicle with a drive auxiliary power system including a 125 cc internal combustion engine. This modification enabled us to extend the range of the hybrid UTV from 50km to 100km per one electric charging.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2236-2245
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• 2009

This paper proposes the process for evaluating the impact of charging the PHEV(Plug-In Hybrid Electric Vehicle) on the distribution systems, and analyzes the study results employing the actual systems as the PHEV is highly expected to increase in the automobile industries in North America in the near future. Since the charging load of the PHEV directly connected to the distribution systems would consume electric power much more than any other existing electric product of residential customers, the new modeling and process would be required to consider the PHEV in distribution systems planning. The EPRI(Electric Power Research Institute) is collaboratively conducting the impact study of PHEV on the distribution systems with power utilities in North America. This study models distribution systems and the charging load of the PHEV using OpenDSS software, and analyzes the impact of PHEV on the distribution systems by assuming various scenarios with different charging time and PHEV types.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.570-572
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• 1999

An equivalent circuit model of vehicle charging-discharging system for simulation is developed. The vehicle electric power system consists of alternator and battery. The alternator must have adequate capacity for providing electric energy to all loads, and the battery supports the alternator by offering insufficient energy when the alternator output energy is not enough. The alternator model is simplified for the use of characteristic curve, which was provided by its manufacturer, and the battery model is separated in charging mode and discharging mode because of its complex characteristics. Developed circuit model is validated by comparing the simulation data and real experimental data.

• Journal of Energy Engineering
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• v.29 no.3
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• pp.64-73
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• 2020

This paper presented a methodology for calculating daily load curves per city by taking into account the charging/discharging location of electric vehicle. In other words, this is the daily load curve calculation algorithm by city, which takes into account the charging/discharging location of electric vehicles, so that the impact of loads generated by charging/discharging of electric vehicles on the power grid can be easily understood in certain cities. Specifically, in accordance with the PEVs share scenario, the PEVs discharge power was calculated to reflect both the characteristics of the arriving vehicle in the morning and the SMP plan after establishing a assumption that the electric vehicle arrived at work in the morning and the electric vehicle arrived at home in the afternoon for each of the charging/discharging locations, that is, work and home, of electric vehicles in the city. After calculating the daily load curve for each charging/discharging power type for the PEVs charging strategy, which takes into account both the characteristics of the vehicle arriving at home in the afternoon and the TOU fare system, it was analyzed by comparing the impact assessment on the grid by adding the existing load.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.150-158
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• 2018

In this paper, we introduce an electric vehicle charging system using power line communication and propose a method to correct the error by applying a deep learning algorithm when an error occurs in the control signal of an electric vehicle charging system using power line communication. The error detection and correction of the control signal can be solved through the conventional error correcting code schemes, but the error is detected and corrected more efficiently by using the deep learning based error correcting code scheme. Therefore, we introduce deep learning based error correction code scheme and apply this scheme to electric vehicle charging system using power line communication. we proceed simulation and confirm performance with bit error rate. we judge whether the deep learning based error correction code scheme is more effective than the conventional schemes.

• Smart Media Journal
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• v.9 no.1
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• pp.67-74
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• 2020

As the demand of electric vehicles has been increased recently, their related industries are developing. In particular, the market of electric vehicles charging infrastructure is expanding rapidly and users have much demand in convenience of electric vehicles charging site. Because an charging site using electric pole of KEPCO can make use of that installed nearby public parking lots, there are many commercial construction and convenient facilities near around it. In this situation, users can do shopping or their personal business during charging. In this paper, we proposed the design of charging platform for electric vehicles to support LBS for users to do shopping or personal business conveniently.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.64-65
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• 2017

This paper review the core technical trends of TESAL EV(Electric Vehicle) Motors. The object of this study analyzes electric vehicle's body appearance, motor cooling system, battery arrangement, battery management system (BMS), and super charging station etc.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.5
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• pp.8-13
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• 2020

In this paper, the electric vehicle (EV) and internal combustion engine vehicle (ICEV) are compared for different driving cases. The EV exhibits a lower powertrain efficiency when driven on the aggressive driving cycle than when driven on the moderate cycle. In particular, EV powertrain efficiency is low when the battery state of charge (SOC) is low, but ICEV efficiency increases when the driving cycle changes from the moderate cycle to the aggressive cycle. Based on these results, attempts can be made to increase EV powertrain efficiency. EV charging before the battery power drops to a low charging state can reduce energy consumption by 2.7% for an urban area. Furthermore, ECO driving has a more significant effect on EVs than on ICEVs.