• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.9
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• pp.1242-1248
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• 2012

Electric vehicle usage is currently very low, but it will be increase with development of electric vehicle technology and a good government policy. Moreover in 2020, advanced electric vehicle manufacturing system will give high performance for its price and mass production. Electric vehicle will become widespread in Korea. From an operational and a planned viewpoint, the electric power demand should be considered in relation to diffusion of electric vehicles. This paper presents the impact of the various battery charge systems. A comparison is performed for electric vehicle charging methods such as, normal charging, fast charging, and battery swapping. In addition, economic evaluation for the replaceable battery system and the quick battery charging system is performed through basic information about charging Infrastructure installation cost. The results of the evaluation show that replaceable battery system is more economical and reliable in side of electric power demand than quick battery charging system.

• KEPCO Journal on Electric Power and Energy
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• v.8 no.2
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• pp.143-149
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• 2022

As ESS safety issues increase recently, there is a need to more precisely monitor the temperature of the ESS. In this paper, DTS technology for temperature monitoring of ESS batteries is introduced and the temperature measurement principle is explained. The temperature of the battery module is measured using the DTS system, and the thermal deviation between battery cells inside the battery module is analyzed. In order to analyze how thermal imbalance affects the charging and discharging performance of the battery, an accelerated degradation test was conducted. Cycle life characteristics analysis, battery surface temperature change, and AC impedance characteristics were conducted to analyze how the performance of battery cells differs according to temperature conditions.

• 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.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.265-273
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• 2017

Recently the Paris Climate Change Accord has been officially put into effect, making global efforts to implement Greenhouse Gas (GHG) reductions, and also International environmental regulations in the automotive sector will be further strengthened. The electric vehicle, which minimizes the particulate matter generated by existing internal combustion engine automobiles, is evaluated as a representative eco-friendly automobile. However, charging the battery of an electric vehicle is not fully environment-friendly if it is fueled by electricity that is being generated by fossil fuels as an energy source. The energy generated by the photovoltaic power generation system, which is an infinite clean energy, can be used to charge an electric vehicle's battery. Currently, shortage of charging facilities, time of charging, and high battery prices are the problem of activating the supply of electric vehicles. This study is to build a conjunction between the EVBSS (Electric Vehicle Battery Supply System) and ESS (Energy Storage System), which can quickly supply the photovoltaic charged battery to the required demand. If the charged battery in the Battery Swapping Station (BSS) is swapped swiftly, it will dramatically shorten the waiting time for charging the battery. As a result, if the battery is rented when it is needed, electric vehicles can be sold without the cost of a battery, which accounts for a large portion of the total cost, then the supply of electric vehicles are expected to expand. Furthermore, it will be an important alternative to maneuver climate change by minimizing GHG emissions from internal combustion engine vehicles.

• Journal of Information Technology Applications and Management
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• v.30 no.1
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• pp.1-9
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• 2023

Interest in the future of the battery market is growing as Tesla announces plans to increase production of electric vehicles and to produce batteries. Tesla announced an action plan to reduce battery prices by 56% through 'Battery Day', which included expansion of factories to internalize batteries and improvement of materials and production technology. In the trend of automobile electrification, the expansion of the battery market, which accounts for 40% of the cost of electric vehicles, is inevitable, and the size of the electric vehicle battery market in 2026 is expected to increase more than five times compared to 2016. With the development of materials and process technology, the energy density of electric vehicle batteries is increasing while the price is decreasing. Soon, electric vehicles and internal combustion locomotives are expected to compete on the same line. Recently, the mileage of electric vehicles is approaching that of an internal combustion locomotive due to the installation of high-capacity batteries. In the EV battery market, Korean, Chinese and Japanese companies are fiercely competing. Based on market share in the first half of 2020, LG Chem, CATL, and Panasonic are leading the EV battery supply, and the top 10 companies included 3 Korean companies, 5 Chinese companies, and 2 Japanese companies. All-solid, lithium-sulfur, sodium-ion, and lithium air batteries are being discussed as the next-generation batteries after lithium-ion, among which all-solid-state batteries are the most active. All-solid-state batteries can dramatically improve stability and charging speed by using a solid electrolyte, and are excellent in terms of technology readiness level (TRL) among various technology alternatives. In order to increase the competitiveness of the battery industry in the future, efforts to increase the productivity and economy of electric vehicle batteries are also required along with the development of next-generation battery technology.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.651-654
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• 2002

Study of electric vehicle is popular with automobile company. However, battery cooling problem has delayed development of electric vehicle. Lifetime of electric vehicle's battery depends on the cooling effect for the battery tray. One model was simulated by 3-D, steady state, incompressible, k-e turbulent model simulation. It is found that flow inlet, outlet and inlet position are very important design parameters.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.85-92
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• 2022

Currently, various researches on electric vehicle battery systems have been conducted from the viewpoint of safety and performance for SoC, SoH, etc. However, it is difficult to build a precise electrical model of a battery system based on the chemical reaction and SoC prediction. Experimental measurements and predictions of the battery SoC were usually performed using dynamometers. In this paper, we construct a simulation model of an electric vehicle system using Matlab Simulink, and confirm the response characteristics based on the vehicle test driving profiles. In addition, we show that it is possible to derive the correlation between the SoC, voltage, and current of the battery according to the driving time of the electric vehicle in conjunction with the BMS model.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.5
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• pp.715-724
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• 2022

In many electric vehicles, large-capacity pouch-type lithium-ion battery packs are mainly used to increase the mileage on a single charge. The lithium ion battery should be operated within the temperature range of 25℃ to 40℃ because the battery performance can be rapidly deteriorated due to an increase in internal temperature. Battery thermal management system (BTMS) can give the suitable temperature conditions to battery by water cooling method. In this research, the heat transfer characteristics (the battery temperature distributions and the water flow characteristics) were analyzed by CFD method to investigate the thermal performance of the cooling plate with 4-pass water flow structure. Moreover, the effect of the presence of fins between the battery cell was identified. The fins made smooth temperature distributions between the battery cells due to the heat spreading and lower the average battery cells temperature.

• Journal of Power Electronics
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• v.12 no.1
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• pp.113-119
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• 2012

This paper describes the design and control of a phase shift full bridge converter with a current doubler, which can be used for the on-board charger for the lead-acid battery of electric forklifts. Unlike the common resistance load, the battery has a large capacitance element and it absorbs the entire converter output ripple current, thereby shortening the battery life and degrading the system efficiency. In this paper a phase shift full bridge converter with a current doubler has been adopted to decrease the output ripple current and the transformer rating of the charger. The charge controller is designed by using the small signal model of the converter, taking into consideration the internal impedance of the battery. The stability and performance of the battery charger is then verified by constant current (CC) and constant voltage (CV) charge experiments using a lead-acid battery bank for an electric forklift.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.385-391
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• 2023

As the use of electric vehicles has increased to minimize carbon emissions, the analyzing the state and performance of lithium-ion batteries that is instrumental in electric vehicles have been important. Comprehensive analysis using not only the voltage, current and temperature of the battery pack, which can affect the condition and performance of the battery, but also the driving data and charging pattern data of the electric vehicle is required. Therefore, a thorough analysis is imperative, utilizing electric vehicle operation data, charging pattern data, as well as battery pack voltage, current, and temperature data, which collectively influence the condition and performance of the battery. Therefore, collection and preprocessing of battery data collected from electric vehicles, collection and preprocessing of data on driver driving habits in addition to simple battery data, detailed design and modification of artificial intelligence algorithm based on the analyzed influencing factors, and A battery analysis and evaluation model was designed. In this paper, we gathered operational data and battery data from real-time electric buses. These data sets were then utilized to train a Random Forest algorithm. Furthermore, a comprehensive assessment of battery status, operation, and charging patterns was conducted using the explainable Artificial Intelligence (XAI) algorithm. The study identified crucial influencing factors on battery status, including rapid acceleration, rapid deceleration, sudden stops in driving patterns, the number of drives per day in the charging and discharging pattern, daily accumulated Depth of Discharge (DOD), cell voltage differences during discharge, maximum cell temperature, and minimum cell temperature. These factors were confirmed to significantly impact the battery condition. Based on the identified influencing factors, a battery analysis and evaluation model was designed and assessed using the Random Forest algorithm. The results contribute to the understanding of battery health and lay the foundation for effective battery management in electric vehicles.