• Journal of the Korean Electrochemical Society
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• v.21 no.4
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• pp.61-67
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• 2018

As emerging the new electric devices, the commercial lithium ion batteries have faced with various challenges. In this regard, many efforts to solve challenges have been tried. In order to solve the above problems in terms of development of a new secondary battery, we successfully demonstrated the two electrocatalysts, such as MCWB and PPY hydrogel, PPY hydrogel and MCWB showed typical H3-type BET isotherm, indicating that micro- and mesopores existed. Especially, in terms of voltage efficiency at the first cycle, PPY hydrogel was higher than that of MCWB, but lower than that of PtC. More interestingly, the PPY hygrogel based seawater battery exhibited charge-discharge reversibility during 20 cycles, and the voltage efficiencies ranged from 70.32 % to 77.35 % in cyclic performance test.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.598-598
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• 2012

Rechargeable lithium-ion batteries have been considered the most attractive power sources for mobile electronic devices. Although graphite is widely used as the anode material for commercial lithium-ion batteries, it cannot fulfill the requirement for higher storage capacity because of its insufficient theoretical capacity of 372 mAh/g. For the sake of replacing graphite, Sn-based materials have been extensively investigated as anode materials because they can have much higher theoretical capacities (994 mAh/g for Sn, 875 mAh/g for SnO, 783 mAh/g for $SnO_2$). However, these materials generate huge volume expansion and shrinkage during $Li^+$ intercalation and de-intercalation and result in the pulverization and cracking of the contact between anode materials and current collector. Therefore, there have been significant efforts of avoiding these drawbacks by using nanostructures. In this study, we present the CVD growth of SnO branched nanostructures on Cu current collector without any binder, using a combinatorial system of the vapor transport method and resistance heating technique. The growth mechanism of SnO branched nanostructures is introduced. The SnO nanostructures are evaluated as an anode for lithium-ion battery. Remarkably, they exhibited very high discharge capacities, over 520mAh/g and good coulombic efficiency up to 50 cylces.

• Journal of Power Electronics
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• v.13 no.4
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• Journal of the Korean Electrochemical Society
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• v.7 no.4
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• pp.189-193
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• 2004

Lithium secondary battery with gel polymer electrolyte, which was composed of POAGA and TEGDMA, was prepared and its cell performances were evaluated. Collation time decreased with increasing the contents of the monomer in the POAGA-based gel polymer electrolyte. The polymer electrolyte was stable up to 4.5V electro-chemically and its ionic conductivity was $5.2\times10^{-3}Scm^{-1}$ at room temperature. The lithium-ion polymer battery with $3.0wt\%$ curable monomer and $1.0wt\%$ monomer showed rate-capability, low-temperature performance and cycleability.

• Journal of Electrochemical Science and Technology
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• v.13 no.1
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• pp.78-89
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• 2022

ANODE-free Li-metal batteries (AFLMBs) operating with Li of cathode material have attracted enormous attention due to their exceptional energy density originating from anode-free structure in the confined cell volume. However, uncontrolled dendritic growth of lithium on a copper current collector can limit its practical application as it causes fatal issues for stable cycling such as dead Li formation, unstable solid electrolyte interphase, electrolyte exhaustion, and internal short-circuit. To overcome this limitation, here, we report a novel dual-salt electrolyte comprising of 0.2 M LiPF₆ + 3.8 M lithium bis(fluorosulfonyl)imide in a carbonate/ester co-solvent with 5 wt% fluoroethylene carbonate, 2 wt% vinylene carbonate, and 0.2 wt% LiNO₃ additives. Because the dual-salt electrolyte facilitates uniform/dense Li deposition on the current collector and can form robust/ionic conductive LiF-based SEI layer on the deposited Li, a Li/Li symmetrical cell exhibits improved cycling performance and low polarization for over 200 h operation. Furthermore, the anode-free LiFePO₄/Cu cells in the carbonate electrolyte shows significantly enhanced cycling stability compared to the counterparts consisting of different salt ratios. This study shows an importance of electrolyte design guiding uniform Li deposition and forming stable SEI layer for AFLMBs.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.2
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• pp.142-147
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• 2005

In this work, a gel polymer electrolyte (GPE) was prepared using polyoxyalkylene glycol acrylate (POAGA) as a macromonomer LiCoO$_2$/GPE/graphite cells were prepared and their electrochemical properties were evaluated at various current densities and temperatures. The ionic conductivity of the GPE was more than 6.2${\times}$10$^{-3}$ S$.$$cm^{-1}$ / at room temperature. The GPE had good electrochemical stability up to 4.5 V vs. Li/Li$^{+}$. POAGA-based cells were showed good electrochemical performances such as rate capability, low-temperature performance, and cycleability. The cells, also, passed a safety test such as the overcharge and nail-penetration test.t.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.635-641
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• 2016

In order to drive a hybrid propulsion device which combines an engine and an electric propulsion unit, battery packs that contain dozens of unit cells consisting of a lithium-based battery are used to maintain the power source. Therefore, it is necessary to more strictly manage a number of battery cells at any given time. In order to manage battery cells, generally voltage, current, and temperature data under load condition are monitored from a personal computer. Other important elements required to analyze the condition of the battery are the internal resistances that are used to judge its state-of-health (SOH) and the open-circuit voltage (OCV) that is used to check the battery charging state. However, in principle, the internal resistances cannot be measured during operation because the parallel equivalent circuit is composed of internal loss resistances and capacitance. In most energy storage systems, battery management system (BMS) operations are carried out by using data such as voltage, current, and temperature. However, during operation, in the case of unexpected battery cell failure, the output voltage of the power supply can be changed and propulsion of the hybrid vehicle and vessel can be difficult. This paper covers the implementation of a high safety battery management system (HSBMS) that can estimate the OCV while the device is being driven. If a battery cell fails unexpectedly, a DC power supply with lithium iron phosphate can keep providing the load with a constant output voltage using the remainder of the batteries, and it is also possible to estimate the internal resistance.

• 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.

• Journal of the Korean Ceramic Society
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• v.54 no.5
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• pp.438-442
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• 2017

This paper reports the facile synthesis of microlamella-structured porous copper (Cu)-oxide-based electrode and its potential application as an advanced anode material for lithium-ion batteries (LIBs). Nanowire-like Cu oxide, which is created by a simple thermal oxidation process, is radially and uniformly formed on the entire surface of Cu foam that has been fabricated using a combination of water-based slurry freezing and sintering (freeze casting). Compared to the Cu foil with a Cu oxide layer grown under the same processing conditions, the Cu foam anode with 63% porosity exhibits over twice as much capacity as the Cu foil (264.2 vs. 131.1 mAh/g at 0.2 C), confirming its potential for use as an anode electrode for LIBs.

• 한국전기화학회:학술대회논문집
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• 2001.04a
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• pp.34-34
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• 2001