• 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.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.864-865
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• 2011

Battery Disconnecting System (BDS) is the important equipment in electric vehicle system. Therefore, most of electric vehicle companies, i.e. Hyundai Motors, Renault Motors, General Motors, want to have the reliability of 15 years - 150, 000 miles. Recently, reliability prediction through Siemens Norm SN 29500 is considered without testing. In this paper, we will introduce the standard and various input parameters. Also the case study will be shown for BDS. Prediction model is constructed by listing all the components of BDS. It calculates the $\pi$ factors for each components using the conversion equation in the standard and converts the reference failure rates to the expected operating failure rates. According to the result, the parts which will be improved are EV-Relays.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.2
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• pp.70-76
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• 2014

In industrial situation, electronic and electro-mechanical systems have been using different type of batteries in rapidly increasing numbers. These systems commonly require high reliability for long periods of time. Wider application of battery for low-power design as a prime power source requires us knowledge of failure mechanism and reliability of batteries in terms of load condition, environment condition and other explanatory variables. Battery life is an important factor that affects the reliability of such systems. There is need for us to understand the mechanism leading to the failure state of battery with performance characteristic and develop a method to predict the life of such battery. The purpose of this paper is to develope the methodology of monitoring the health of battery and determining the condition or fate of such systems through the performance reliability to predict the remaining useful life of primary battery with load condition, operating condition, environment change in light of battery life variation. In order to evaluate on-going performance of systems and subsystems adopting primary batteries as energy source, The primitive prototype for performance reliability analysis device was developed and related framework explained.

• 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.

• International Journal of Reliability and Applications
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• v.12 no.2
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• pp.123-129
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• 2011

Due to restriction of vehicle emissions and high demand for fossil fuels nowadays, car manufacturers around the world are looking into alternative ways in introducing new car model that would vastly captured the market. Thus, Electric Vehicle (EV) has been further developed to take the advantage of the current global issues on price of fossil fuels and impact on the environment. Since car battery plays the crucial role on the overall performance of EV, many researchers have been working on improving the component. This paper focused on the reliability of EV battery which involves recognizing failure types, testing method and life prediction method. By focusing on these elements, the reliability feature being identified and as a result the batteries life will be prolonged.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.129-134
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• 2023

Although the use of batteries is rapidly increasing worldwide to improve carbon neutrality and energy efficiency, performance degradation due to the increase in the number of uses is inevitable as it is a finite resource that can be applied according to capacity and specifications. Deterioration and failure of batteries are recognized as important problems in various applications using batteries, including electric vehicles. In order to solve these problems, a diagnostic technology capable of accurately predicting battery life and grasping state information is required, but it is difficult in a non-linear form due to internal structure or chemical change. In this paper, the factors that generally cause battery performance change are directly applied to check whether there are external changes and impedance changes in the battery, and to analyze whether they affect battery life. Impedance change trends and result values were confirmed using a universal impedance spectroscopy method and a self-developed internal impedance measurement method. The results did not significantly affect the impedance change trend. It was confirmed that the increase in the number of times of battery use was prominent in the impedance change trend.

• Journal of Internet Computing and Services
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• v.9 no.5
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• pp.165-173
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• 2008

Hybrid ad hoc networks are integrated networks referred to Home Networks, Telematics and Sensor networks can offer various services. Specially, in ad hoc network where each node is responsible for forwarding neighbor nodes' data packets, it should net only reduce the overall energy consumption but also balance individual battery power. Unbalanced energy usage will result in earlier node failure in overloaded nodes. it leads to network partitioning and reduces network lifetime. Therefore, this paper studied the routing protocol considering efficiency of energy. The suggested algorithm can predict the status of energy in each node using the energy prediction model. This can reduce the overload of establishing route path and balance individual battery power. The suggested algorithm can reduce power consumption as well as increase network lifetime.

• 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.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.7-17
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• 2014

Objective of this paper is to introduce a new technology known as prognostics and health management (PHM) which enables a real-time life prediction for safety critical systems under extreme loading conditions. In the PHM, Bayesian framework is employed to account for uncertainties and probabilities arising in the overall process including condition monitoring, fault severity estimation and failure predictions. Three applications - aircraft fuselage crack, gearbox spall and battery capacity degradation are taken to illustrate the approach, in which the life is predicted and validated by end-of-life results. The PHM technology may allow new maintenance strategy that achieves higher degree of safety while reducing the cost in effective manner.

• 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.