• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.1
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• pp.71-78
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• 2020

In the case of power generation using renewable energy, power production may not be smooth due to the influence of the weather. The energy storage system (ESS) is used to increase the efficiency of solar and wind power generation. ESS has been continuously fired due to a lack of battery protection systems, operation management, and control system, or careless installation, leading to very big casualties and economic losses. ESS stability and battery protection system operation management technology is indispensable. In this paper, we present a battery level calculation algorithm and a failure prediction algorithm for ESS optimization and stable operation. The proposed algorithm calculates the correct battery level by accumulating the current amount in real-time when the battery is charged and discharged, and calculates the battery failure by using the voltage imbalance between battery cells. The proposed algorithms can predict the exact battery level and failure required to operate the ESS optimally. Therefore, accurate status information on ESS battery can be measured and reliably monitored to prevent large accidents.

• 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 IKEEE
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• v.23 no.1
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• pp.254-260
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• 2019

The failure rate of bidirectional dc-to-dc converter is predicted through the failure mode and effect analysis (FMEA) and the fault-tree analysis (FTA) considering the operational risk. In order to increase the driving voltage of the electric vehicle efficiently, the bidirectional converter is attached to the front of the inverter. It has a boost mode for discharging battery power to the dc-link capacitor and a buck mode for charging the regenerative power to the battery. Based on the results of the FMEA considering the operating characteristics of the bidirectional converter, the fault-tree is designed considering the risk of the converter. After setting the design parameters for the MCU for the electric vehicle, we analyze the failure rate of the capacitor due to the output voltage ripple and the inductor component failure rate due to the inductor current ripple. In addition, we obtain the failure rate of major parts according to operating temperature using MIL-HDBK-217F. Finally, the failure rate and the mean time between failures (MTBF) of the converter are predicted by reflecting the part failure rate to the basic event of the fault-tree.

• Proceedings of the Safety Management and Science Conference
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• 2011.04a
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• pp.407-417
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• 2011

기술 발전 속도가 빨라짐에 따라 부품의 개발기간이 단축되고 있다. 더욱이 최근에는 제품들의 신뢰성이 향상되어 가속수명시험을 실시하더라도 규정된 시험 시간 동안 고장을 발견할 수 없는 경우가 많이 발생하고 있다. 또한 현업에서는 성능열화에 대한 관심이 높아지고 있으며 특히 친환경차에 대한 관심이 많아지면서 연료전지 및 납-배터리의 가속열화시험법개발에 많은 관심이 증대되고 있다. 만약 고장이 발생하지 않는다고 해서 더 가혹한 스트레스를 인가하면 전혀 다른 고장 메커니즘이 나타날 수 있기 때문에 시험의 목적을 달성하기 곤란해진다. 따라서 이런 단점을 보완하기 위해 시간에 따라 정해진 시간마다 열화 특성을 갖는 특성치를 측정하여 수명을 예측하거나 신뢰성을 평가하는 열화시험, 가속열화시험을 이용한다. 본 연구는 열화데이터 분석 방법을 정리하여 현업에 적용 가능한 분석 과정을 제안하고 향후 연료전지 및 납-배터리 가속열화시험 적용방향을 제시하고자 한다.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.12
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• pp.819-828
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• 2022

Sensitivity of aircraft sizing depending on battery performance was studied for a generic quad tilt rotor type electric vertical takeoff and landing vehicle. The mission requirements proposed by Uber Elevate and NASA were used for initial sizing, and the calculated gross weight is ranged between 5,000lb and 11,000lb for battery specific energy range of 200-400Wh/kg in pack level and continuous discharge rate range of 4-5C. For the assumed gross weight of 7,000lb, the required battery performance was calculated with two different criteria: available power and energy, and the effects of battery specific energy and discharge rate are analyzed. The maximum discharge rate is also recommended considering failure cases such as one battery pack inoperative and one prop rotor inoperative.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.4
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• pp.313-322
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• 2013

Batteries, which are being used as energy sources in various applications, tend to degrade, and their capacity declines with repeated charging and discharging cycles. A battery is considered to fail when it reaches 80% of its initial capacity. To predict this, prognosis techniques are attracting attention in recent years in the battery community. In this study, a method is proposed for estimating the battery health and predicting its remaining useful life (RUL) based on the slope of the charge voltage curve. During this process, a Bayesian framework is employed to manage various uncertainties, and a Particle Filter (PF) algorithm is applied to estimate the degradation of the model parameters and to predict the RUL in the form of a probability distribution. Two sets of test data-one from the NASA Ames Research Center and another from our own experiment-for an Li-ion battery are used for illustrating this technique. As a result of the study, it is concluded that the slope can be a good indicator of the battery health and PF is a useful tool for the reliable prediction of RUL.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.12
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• pp.21-27
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• 2020

Lithium-ion batteries are the heart of energy-storing devices and electric vehicles. Owing to their superior qualities, such as high capacity and energy efficiency, they have become quite popular, resulting in an increased demand for failure/damage prevention and useable life maximization. To prevent failure in Lithium-ion batteries, improve their reliability, and ensure productivity, prognosticative measures such as condition monitoring through sensors, condition assessment for failure detection, and remaining useful life prediction through data-driven prognostics and health management approaches have become important topics for research. In this study, the residual useful life of Lithium-ion batteries was predicted using two efficient artificial recurrent neural networks-ong short-term memory (LSTM) and gated recurrent unit (GRU). The proposed approaches were compared for prognostics accuracy and cost-efficiency. It was determined that LSTM showed slightly higher accuracy, whereas GRUs have a computational advantage.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.2
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• pp.192-200
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• 1999

위성의 전지는 위성의 수명과 직접적인 영향을 갖고 있으며 이것의 정상동작여부에 따라 위성의 안정적인 임무수행여부가 결정된다. 상대적으로 일반화된 셀 모델링의 최근 개발은 NiH2셀의 동특성을 시뮬레이션 하기 위한 기본적인 원리에 기반을 둔 접근방식이다. 그러나 이러한 일반적인 방정식을 통해 비선형성과 전력상태를 포함하는 전지 특성을 예측하는 것은 사실상 불가능하다. 본 연구에서는 다층신경회로망을 이용하여 비선형 특성를 갖는 니켈-하이드로진 전지 특성을 모델링 하였으며, 모델링된 상수값은 위성의 식시간 동안의 전지 전력상태 분석을 위해 사용되었다. 모델링 결과의 정확성을 확인하기 위해 니켈-하이드로진 전지시험결과 분석자료와 비교 검토 되었다. 전지 동작모드는 정상동작모드와 실패모드로 나누어 분석되었다. 정상동작모드는 위성의 식시간 동안 아크젯 동작 여부에 의해 각각 분석되었으며, 또한 태양전지와 배터리 셀 일부의 고장으로 인한 실패모드에서의 전지전력상태가 분석되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.59-61
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• 2021

The electric propulsion development is underway to minimize pollutants and greenhous gas emissions during the operation of ships / offshore installation vessels. The importance of the use and efficient management of batteries, which is an ESS system in ships / offshore installation vessels, is increasing. Generally, in ESS where battery is applied, cell balancing and life span are monitored in real time by BMS. Ships / offshore installation vessel are equipped with several ESS rooms, and ESS rooms with ESS systems of the same specification are being constructed due to the recent demand for electric propulsion development. In this paper, we propose an algorithm to additionally predict and diagnose battery pack and cell balancing failures by comparing BMS data for each rooms. The proposed algorithm compares the BMS data of each ESS Room according to the environmental change of the ship / offshore installation vessels, measures accurate status information, and reliably monitors it to prevent accidents in advance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.5899-5905
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• 2014

Faults in electric power system can be a critical problem for vehicles. The system durability is determined mainly by the durability of their components and operating conditions. Monitoring the conditions of the electric power system may be necessary because it is very difficult to predict precisely when it will fail. Therefore, the aim of this study was to develop a diagnosis system for an electric power system of a vehicle. The alternator voltage, excitation voltage, lamp voltage, battery voltage, and engine rpm from a crank angle sensor are monitored continuously and the system fault can be then detected in real time. NI USB- 9201 DAQ and LabVIEW SW have been used to measure the voltages and analyze the data. Compared to conventional measurements for only each component, an integrated and portable measurement method was developed. In addition to the monitoring the electric power system in real time, the saved data from the measurement also provides valuable information to improve the durability of the components.