• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.228-236
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• 2022

The charging methods of electric vehicles are divided into wired charging and wireless charging. Restrictions on the use of charging infrastructure for wireless charging vehicles currently exist because most charging infrastructure uses the wired charging method. Thus, wired and wireless integrated charging system has been studied. In this system, a wireless charging system especially requires a control method for high-efficiency operation in consideration of a change in a coupling coefficient. Therefore, this paper introduces two control methods for the high-efficiency operation of wireless charging that can be applied to wired and wireless integrated charging systems. In addition, loss analysis is performed through PSIM simulation to select a more advantageous method for high-efficiency operation among the two control methods. To verify the simulation-based loss analysis result, the two control methods are applied to the actual wireless charging system, and the efficiency is compared through the experiments Based on the experimental results, a control method suitable for high-efficiency operation of the wireless charging method is selected.

• Journal of the Semiconductor & Display Technology
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• v.20 no.3
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• pp.136-139
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• 2021

In this paper, we studied the charging characteristics of high-capacity supercapacitor with high current for RF wireless charging system for smart phone charging. The dc output of the RF-DC receiver is connected to supercapacitor after which is connected to DC-DC converter for charging a smart phone. This configuration stably supplies voltage and current for charging it. Studies show that the higher charging current use, the rapidly shorter the charging time of supercapacitor is. The currents of 2A, 10A and 27A were used for charging supercapacitors. The charging time was measured for 3000F, 6000F, 12000F supercapacitors which is parallelly connected with 3000F supercapacitors.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.8
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• pp.432-441
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• 2000

It is difficult to analyze the charging characteristics of the lead-acid battery, because of the influences by various non-linear and time-variant parameters. In this study, the charging characteristics of high capacity industrial lead-acid battery 630 Ah was investigated through experiments with respect to the variations of temperature and the aged state of battery during the charging process. The database of those characteristics is established from the results of experiments, and the fuzzy logic charging algorithm is suggested using them. The results of experiment shows that the industrial lead-acid batteries can be always fully charged within the saved charging time by the proposed charging control algorithm adapting to the variations of charging condition. This new charging concept will be useful for developing the advanced battery charger improving the efficiency of storing electricity.

• Journal of the Semiconductor & Display Technology
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• v.20 no.2
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• pp.29-33
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• 2021

A 5.8-GHz 1W wireless power transmission system was used for charging a smart phone. The voltage of one RF power receiver with antenna was not enough for charging. Several power receivers for charging a smart phone was connected serially. The voltage of several RF power receivers are highly enough for charging a smart phone within 50cm. However, the lack of current from small capacitances of RF-DC converters is not suitable for charging smart phone. It means very long charging time. In this paper, the voltage multiplier circuits for RF-DC converters were analyzed to increase the current and voltage at the same time to reduce the charging time in smartphone RF wireless charging. Through the analysis of multiplier circuits, the 7-stage parallel multiplier circuit with voltage-doubler units are suitable for charging the smartphone, which supplies 5V and 700mA at 3V@5.8GHz.

• 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.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.810-819
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• 2016

Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.205-214
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• 2013

In this paper, we analyzed the various EV charging-infra information(charging status, charging pattern, charging rate, charging fee, etc.) through the charging infra simulator which would be of help to effectively construct the EV charging infrastructure. The proposed simulator virtually made the EV motoring pattern referred to TMS(Traffic Monitoring System) & Ministry of Land, Transport and Maritime Affairs, and analyzed the charging-infra information(amount of charging, accumulated charging fee, etc.) based on vehicle types, charging type, time and days using EV charging-fee list noticed by KEPCO. Through this simulator, we deducted some considerable contents to build the EV charging infrastructure similarly with real environment.

• Proceedings of the KSR Conference
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• 2010.06a
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• pp.1855-1860
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• 2010

Electric vehicles have reached a new level of development with introductions by Chrysler, Ford, Honda and Toyota. Today's charging technology includes conductive and inductive charging systems. There are three standardized charging levels: Level 1: charging can be done from a standard, grounded AC 120V, 3-prong outlet available in all homes; Level 2: charging is at AC 240V, 40 amp charging station with special consumer features to make it easy and convenient to plug in and charge EVs at home or at an EV charging station; Level 3: a high-powered charging "fast charge" technology currently under development that will provide a charge in less than 15 minutes. The incoming AC power is converted to DC and stored in the vehicle's batteries. In this paper, we investigated the application of urban railway DC electric power for electric car charging system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.3
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.