• 한국재료학회지
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• 제29권12호
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• pp.798-803
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• 2019

The self-discharge behavior of zinc-air batteries is a critical issue induced by corrosion and hydrogen evolution reaction (HER) of zinc anode. The corrosion reaction and HER can be controlled by a gelling agent and concentration of potassium hydroxide (KOH) solution. Various concentrations of KOH solution and polyacrylic acid have been used for gel electrolyte. The electrolyte solution is prepared with different concentrations of KOH (6 M, 7 M, 8 M, 9 M). Among studied materials, the cell assembled with 6 M KOH gel electrolyte exhibits the highest specific discharge capacity and poor capacity retention. Whereas, 9 M KOH gel electrolyte shows high capacity retention. However, a large amount of hydrogen gas is evolved with 9 M KOH solution. In general, the increase in concentration is related to ionic conductivity. At concentrations above 7 M, the viscosity increases and the conductivity decreases. As a result, compared to other studied materials, 7 M KOH gel electrolyte is suitable for Zn-air batteries because of its higher capacity retention (92.00 %) and specific discharge capacity (351.80 mAh/g) after 6 hr storage.

• Journal of Electrochemical Science and Technology
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• 제11권1호
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• pp.1-13
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• 2020

As research on secondary batteries becomes important, interest in analytical methods to examine the condition of secondary batteries is also increasing. Among these methods, the electrochemical impedance spectroscopy (EIS) method is one of the most attractive diagnostic techniques due to its convenience, quickness, accuracy, and low cost. However, since the obtained spectra are complicated signals representing several impedance elements, it is necessary to understand the whole electrochemical environment for a meaningful analysis. Based on the understanding of the whole system, the circuit elements constituting the cell can be obtained through construction of a physically sound circuit model. Therefore, this mini-review will explain how to construct a physically sound circuit model according to the characteristics of the battery cell system and then introduce the relationship between the obtained resistances of the bulk (R_b), charge transfer reaction (R_ct), interface layer (R_SEI), diffusion process (W) and battery characteristics, such as the state of charge (SOC), temperature, and state of health (SOH).

• 한국군사과학기술학회지
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• 제14권4호
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• pp.740-746
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• 2011

Thermally activated batteries have good stability, reliability and long shelf life. Due to these characteristics and operational mechanism, thermal batteries are usually applied to military power sources. Especially, Li/$FeS_2$ thermal batteries, which are used mostly in these days, use LiCl-KCl and LiBr-LiCl-LiF as electrolytes. The electrochemistry of thermal batteries have been researched for long time, however, electrochemical study using impedance spectroscopy was not published so much. Through this research, microscopic electrochemical research was investigated with electrochemical impedance spectroscopy(E.I.S). Electrolyte effects on Li/$FeS_2$ thermal battery was researched changing electrolytes, LiCl-KCl and LiBr-LiCl-LiF. Additionally, the salts, which are added to electrolytes, effects on thermal battery were researched. It is expected that the impedance spectroscopy analysis is applicable to not only thermal battery electrochemical study effectively, but also, thermal battery developments.

• Journal of Power Electronics
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• 제17권5호
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• pp.1288-1297
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• 2017

The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

• Applied Microscopy
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• 제47권2호
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• pp.77-83
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• 2017

Drastic development of ubiquitous devices requires more advanced batteries with high specific capacitance and high rate capability. Large-area microstructure characterization across the stacks of cathode, electrolyte and anode might reveal the origin of the instability or degradation of batteries upon cycling charge. In this study, sample preparation methods to observe the cross-section view of the electrodes for battery in SEM and several imaging tips are reviewed. For an accurate evaluation of the microstructure, ion milling which flats the surface uniformly is recommended. Pros and cons of cross-section polishing (CP) with Ar ion and focused ion beam (FIB) with Ga ion were compared. Additionally, a modified but new cross-section milling technique utilizing precision ion polishing system (PIPS) which can be an alternative method of CP is developed. This simple approach will make the researchers have more chances to prepare decent large-area cross-section electrode for batteries.

• 공업화학
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• 제8권6호
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• pp.1034-1040
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• 1997

전기자동차의 동력원으로 사용되는 90Ah급 Nickel/Metal hydride 전지 11개로 구성된 module의 온도특성을 상용 software인 NISA II를 사용하여 해석하였다. 전지 module에 대한 element수를 감축하기 위하여 열전도도가 다른 여러 층을 통하여 전달되는 열흐름에 대한 해석을 전기저항 등가식을 사용하여 단순화하였으며, Cartesian coordinate의 축별로 다른 열전도도를 삽입하는 orthotropic model을 사용하였다. 전지 module의 온도를 낮추기 위하여 알루미늄 재질의 cooling fin을 전지와 전지사이에 삽입하여 실험을 수행하였고, 전지 module 최외곽에 위치한 fin에 의한 최고온도의 강하 효과는 미미하다는 결과를 얻었다. 전지 module내 전지별 온도차이를 극소화하기 위하여 cooling fin의 개수와 두께 그리고 측면 fin의 복합적인 영향에 대한 실험을 수행하였으며, 1mm 두께의 알루미늄 fin을 4개 사용하여 module내 전지별 최고온도의 차이를 $3^{\circ}C$ 이내로 줄일 수 있었다.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 추계학술대회
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• pp.216-217
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• 2019

The battery powered electric vehicle (EV) is one of most promising technologies in 21^st century. Though the lithium batteries are playing an important role in the EVs, they are only applicable until their capacities reach 80%, the end of its useful first life. Yet, these batteries can live a second life such as Energy Storage Systems (ESS). In order to utilize the Residual Useful Life (RUL) of the batteries the State of Health (SOH) of them needs to be estimated by a nondestructive test such as Electrochemical Impedance Spectroscopy (EIS) technique. Though many kinds of different EIS instruments are commercially available, most of them can only test a battery module less than 10V and the price of the instrument is very high. In this paper a low-cost EIS instrument suitable for measuring the impedance spectrum of the high voltage battery module is proposed and its validity is verified through the experiments. In order to prove the accuracy of the developed EIS instrument its measured impedance spectrum is compared with the results obtained by a commercial instrument. The Chi Square value calculated between two impedance spectrum measured by both developed and commercial instruments are less than 2%, which prove the strong correlation between two results.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2019년도 추계학술대회
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• pp.70-72
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• 2019

For the safe and reliable operation of Lithium-ion batteries in Electric Vehicles (EVs) or Energy Storage Systems (ESSs), it is essential to have accurate information of the battery such as State of Charge (SOC). Many kinds of different techniques to estimate the SOC of the batteries have been developed so far such as the Kalman Filter. However, when it is applied to the multiple number of batteries it is difficult to maintain the accuracy of the estimation over all cells due to the difference in parameter value of each cell. Moreover the difference in the parameter of each cell may become larger as the operation time accumulates due to aging. In this paper a novel Deep Neural Network (DNN) based SOC estimation method for multi cell application is proposed. In the proposed method DNN is implemented to learn non-linear relationship of the voltage and current of the lithium-ion battery at different SOCs and different temperatures. In the training the voltage and current data of the Lithium battery at charge and discharge cycles obtained at different temperatures are used. After the comprehensive training with the data obtained with a cell resulting estimation algorithm is applied to the other cells. The experimental results show that the Mean Absolute Error (MAE) of the estimation is 0.56% at 25℃, and 3.16% at 60℃ with the proposed SOC estimation algorithm.

• Bulletin of the Korean Chemical Society
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• 제34권1호
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• pp.79-88
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• 2013

$LiFePO_4$ is a promising active material (AM) suitable for use in high performance lithium-ion batteries used in automotive applications that require high current capabilities and a high degree of safety and reliability. In this study, an optimization of the electrode design parameters was performed to produce high capacity lithium-ion batteries based on $LiFePO_4$/graphite electrodes. The electrode thickness and porosity (AM density) are the two most important design parameters influencing the cell capacity. We quantified the effects of cathode thickness and porosity ($LiFePO_4$ electrode) on cell performance using a detailed one-dimensional electrochemical model. In addition, the effects of those parameters were experimentally studied through various coin cell tests. Based on the numerical and experimental results, the optimal ranges for the electrode thickness and porosity were determined to maximize the cell capacity of the $LiFePO_4$/graphite lithium-ion batteries.

• 전기학회논문지
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• 제61권8호
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• pp.1099-1106
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• 2012

Microgrid is a new electrical energy system that composed of various generators, renewable energy, batteries and loads located near the electrical customers. When Microgrid is interconnected with large power system, Microgrid don't need to control the frequency. But in case of the outage or faults of power system, Microgrid should control the frequency to prevent the shutdown of Microgrid. This paper presents the frequency control methods using the droop function, being used by synchronous generators and EMS(Energy Management System). Using droop function, two battery systems could share the load based on locally measured signals without any communications between batteries. Also, we suggest that EMS should control the controllable distributed generators as P/Q control modes except batteries to overcome the weakness of droop function. Finally we suggest the two batteries systems to prolong the battery's life time considering the economical view. The validation of proposed methods is tested using PSCAD/EMTDC simulations and field test sites at the same time.