• Journal of the Korean Society of Industry Convergence
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• v.21 no.6
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• pp.329-335
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• 2018

In an electric vehicle and Energy Storage System(ESS), a large number of batteries are connected in series or parallel to obtain high voltage and current. The battery management system(BMS) is needed because battery has a characteristic that explode in overcharging and overcurrent situations due to the nature of the battery material and the battery life is dramatically reduced when the battery is overdischarged below the specified voltage. In this paper, we proposed a system that can manage a large amount of batteries through the communication of master-slave type with multiple microcontroller. We confirmed the stable operation of the proposed system through the balancing-charging and storage mode experiments.

• Journal of Power Electronics
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• v.13 no.3
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• pp.497-506
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• 2013

This paper proposes a new method to improve the available battery capacity in electric vehicles by connecting lead-acid batteries with lithium-ion battery in parallel to supply power. In addition, this method combines the discharge characteristics of batteries to improve their efficiency and lower their cost for electric vehicles. A lithium-ion battery set is used to connect with N sets of lead-acid batteries in parallel. The lead-acid battery supplies the initial power. When the lead-acid battery is discharged by the load current until its output voltage drops to the cut-off voltage, the power management unit controls the lead-acid battery and changes it to discharge continuously with a small current. This discharge can be achieved by connecting the lead-acid battery to a lithium-ion battery in parallel to supply the load power or to discharge its current to another lead-acid or lithium-ion battery. Experimental results demonstrates that the available capacity can be improved by up to 30% of the rated capacity of the lead-acid batteries.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1998.11a
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• pp.177-180
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• 1998

To manage lead-acid battery efficiently and to use it longer in UPS, the state of charge(SOC) indicator of the battery is needed. So a new approach to developing battery SOC indicator for UPS is discussed in this paper. This method to determining SOC by combining the available data of discharge characteristics of a battery with neural networks(NN) is presented. The 3-layered NN with back propagation algorithm has been used. Exprement results show that the proposed method is appropriate as SOC indicator of the battery.

• Transactions of the Korean hydrogen and new energy society
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• v.15 no.1
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• pp.1-11
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• 2004

Hybrid power systems with fuel cells and batteries have the potential to improve the operation efficiency and dynamic response. A proper load management strategy is important to better system efficiency and endurance in hybrid systems. In this paper, a fuzzy logic algorithm has been used to determine the fuel cell output power depending on the external required power and the battery state of charge(SoC). If the required power of the hybrid system is small and the SoC is small, then the greater part of the fuel cell power is used to charge the battery pack. If the required power is relatively big and the SoC is big, then fuel cell and battery are concurrently used to supply the required power. These IF-THEN operation rules are implemented by fuzzy logic for the energy management system of hybrid system. The strategy is evaluated by simulation. The results show that fuzzy logic can be effectively used to optimize the operational efficiency of hybrid system and to maintain the battery SoC properly.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.16 no.2
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• pp.7-12
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• 2020

The battery of an electric vehicle is a key part of the energy supply to operate the vehicles. There are many factors affecting battery life such as charging method, discharge rate, and ambient temperature those are requires systematic monitoring and management. To solve the issues like environmental problems and fuel consumption reduction the battery needs more performance improvement. In this study, it was analyzed the thermal characteristics and securing battery stability for electric vehicle battery cooling system. The simulation test was operated using GT-suite software with several conditions like cooling capacity 1, 2 and 4 kW, cooling flow rate 5, 10, 20 and 30 LPM, and battery initial temperatures 40, 35, and 30℃ at the temperature of ambient 25℃. The results shown that the case of cooling flow rate at 20 LPM was most efficient among all above conditions.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.4
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• pp.351-359
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• 2014

This paper introduces the lithium ion battery system for LEO(Low Earth Orbit) small satellites. This study proves the reliability of lithium ion batteries applying to the space application. The specifications for lithium ion battery unit are proposed to supply power to the satellite and the overall mechanical design including structural simulation to confirm the reliability of the lithium ion BMS(Battery Management System) under the space environment and launching conditions. The results of structural simulation, functional tests, and space environmental tests show the lithium ion battery system is space qualified. Space qualification of the small satellite battery system to secure reliability of BMS and lithium ion batteries lend credibility for using lithium ion batteries in space application.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.7
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• pp.515-520
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• 2018

A large number of lithium-ion batteries are arranged in series and parallel in battery packs, such as those in electric vehicles or energy storage systems. As battery packs age, their output power and energy density drop because of voltage deviation, constant and non-uniform exposure to abnormal environments, and increased contact resistance between batteries; this reduces application system efficiency. Despite the balancing circuit and logic of the battery management system, the output of the battery pack is concentrated in the most severely aged unit cell and the output is frequently limited by power derating. In this study, we implemented a cell imbalance detection algorithm and selected parameters to detect a sudden decrease in battery pack output. In addition, we propose a method to increase efficiency by applying the measured testing values considering the operating conditions and abnormal conditions of the battery pack.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.939-949
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• 2017

Prognostics and health management(PHM) is actively utilized by industry as an essential technology focusing on accurately monitoring the health state of a system and predicting the remaining useful life(RUL). An effective PHM is expected to reduce maintenance costs as well as improve safety of system by preventing failure in advance. With these advantages, PHM can be applied to the battery system which is a core element to provide electricity for devices with mobility, since battery faults could lead to operational downtime, performance degradation, and even catastrophic loss of human life by unexpected explosion due to non-linear characteristics of battery. In this paper we mainly review a recent progress on various models for predicting RUL of battery with high accuracy satisfying the given confidence interval level. Moreover, performance evaluation metrics for battery prognostics are presented in detail to show the strength of these metrics compared to the traditional ones used in the existing forecasting applications.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.22-28
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• 2017

The performance of lithium ion batteries used in electric vehicles (EV) varies greatly depending on the battery temperature. In this paper, the finite difference method was used to evaluate the temperature change, state of charge (SOC), internal resistance, and voltage change of the battery due to heat generation in the battery. The simulation model was linked with AMESim to calculate the driving range of an EV traveling in New European Driving Cycle (NEDC) mode. As the temperature dropped below $25^{\circ}C$, the internal resistance of the battery increased, which increased the amount of heat generated and decreased the driving range of EV. At battery temperatures above $25^{\circ}C$, the driving range was also decreased due to reduced SOC that deteriorated the battery performance. The battery showed optimal performance and the driving range was maximized at $25^{\circ}C$. When battery temperatures of $-20^{\circ}C$ and $45^{\circ}C$, the driving range of EV decreased by 33% and 1.8%, respectively. Maintaining the optimum battery temperature requires heating the battery at low temperature and cooling it down at high temperature through efficient battery thermal management. Approximately 500 W of heat should be supplied to the battery when the ambient temperature is $-20^{\circ}C$, while 250 W of heat should be removed for the battery to be maintained at $25^{\circ}C$.