• Economic and Environmental Geology
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• v.57 no.1
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• pp.83-91
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• 2024

According to the IEA (2022), global rechargeable battery demand is expected to reach 1.3 TWh in 2040. EV batteries will account for about 80% of this demand, and used EV batteries are expected to be discharged after 30 years. Used EV batteries can be recycled and reused to create new value. They can also resolve one of the most vulnerable parts of the battery supply chain: raw material insecurity. In this study, we analyzed the amount of used batteries generated by EV in Korea and their potential for reuse and recycling. As a result, it was estimated that the annual generation of used batteries for EV began to increase to more than 100,000 in '31 and expanded to 810,000 in '45. In addition, it was found that the market for recycling EV batteries in '45 could be expected to be equivalent to the production of 1 million batteries, and the market for reuse could be expected to be equivalent to the production of 36 Gwh of batteries. On the other hand, according to the plan standard disclosed by the recycling company, domestic used EV batteries can account for 11% of the domestic recycling processing capacity (pre-treatment) ('30). So it will be important to manage the import and export of used batteries in terms of securing raw materials.

• Journal of the Korean Society of Industry Convergence
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• v.24 no.6_1
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• pp.669-681
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• 2021

As the supply of xEV in Korea is rapidly increasing, the amount of waste batteries is expected to increase rapidly, but the current recycling system for waste xEV batteries is very insufficient. In order to properly utilize the xEV reusable battery module, it is essential to classify it into a type that has similar discharge characteristics to the current state of health(SOH), which is the discharge capacity of the battery. This paper proposes a system that can minimize the exchange of energy with the KEPCO system by using the charging/discharging method by circulating power between batteries in order to minimize the power consumption when charging and discharging waste batteries. In the proposed system, a function to measure parameters during the charging/discharging test of the waste battery was implemented to build a customized big date for the test waste battery. In addition, the dynamic characteristics of the proposed circuit were analyzed using PSIM, which is useful for power electronics analysis, and the validity of the proposed circuit was verified through experiments.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.3
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• pp.139-146
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• 2019

As the number of electric vehicles (EVs) in Jejudo Island increases, the secondary use of EV batteries is becoming increasingly mandatory not only in reducing greenhouse gas emissions but also in promoting resource conservation. For the secondary use of EV batteries, their capacity and performance at the end of automotive service should be evaluated properly. In this study, the battery state information from the on-board diagnostics or OBD2 port was acquired in real time while driving three distinct routes in Jejudo Island, and then the battery operating characteristics were assessed with the driving routes. The route with higher altitude led to higher current output, i.e., higher C-rate, which would reportedly deteriorate state of health (SOH) faster. In addition, the SOH obtained from the battery management system (BMS) of a 2017 Kia Soul EV with a mileage of 55,000 km was 100.2%, which was unexpectedly high. This finding was confirmed by the SOH estimation based on the ratio of the current integral to the change in state of charge. The SOH larger than 100% can be attributed to the rated capacity that was lower than the nominal capacity in EV application. Therefore, considering the driving environment and understanding the SOH estimation process will be beneficial and necessary in evaluating the capacity and performance of retired batteries for post-vehicle applications.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.6
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• pp.467-473
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• 2001

BMS(Battery Management System) in EV system(Electric Vehicle) senses voltage, temperature and the charging or discharging current of batteries. The main roles of BMS are to estimate SOC(State OF Charge) of batteries and optimally monitor them according to the operation state of EV system which is motoring mode or charging mode. In this paper, we propose the proper algorithm about BMS's roles and operation which is suitable to EV system and illustrate validity and effectiveness through the experiments which were performed in the condition of Vehicle road test and charging test.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.3
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• pp.67-77
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• 2024

Increasing energy efficiency in factories is an activity aimed at optimizing resource allocation in manufacturing processes to establish production plans. However, this strategy may not apply effectively when night shifts are unavoidable. Additionally, continuous fluctuations in production requirements pose challenges for its implementation in the factory. Recently, with the rapid proliferation of electric vehicles (EVs), technology utilizing electric vehicle batteries as energy storage systems has gained attention. Technology using these batteries can be an alternative for factory energy management. In this paper, a factory energy management method using EV batteries is proposed. The proposed method is analyzed using PSCAD/EMTDC software, considering the state of charge of EV batteries and Time-of-Use (TOU) rates. The proposed method was compared with production scheduling established considering predicted power usage and TOU rates. As a result, production scheduling saved 4,152 KRW per day, while the proposed method saved 7,286 KRW in electricity costs. Through this paper, the possibility of utilizing EV batteries for factory energy management has been demonstrated.

• Proceedings of the KIPE Conference
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• 2018.07a
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• pp.489-490
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• 2018

As the number of electric vehicles (EV) increases, there is an increasing interest in the post-vehicle application of the EV batteries. For the second use application of EV batteries, the state of health (SOH) at the end of automotive service has to be evaluated differently from the automotive perspective. It will be helpful to consider the driving conditions of EVs in understanding the performance deterioration trend of the battery. In this paper, we acquired the battery status information in real time during driving and compared the characteristics by the driving routes. The SOH from the BMS can be rescaled to percentage ratio to give a more general idea about the performance degradation.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.236-241
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• 2024

Due to the recent emphasis on carbon neutrality and environmental regulations, the global electric vehicle (EV) market is experiencing rapid growth. This surge has raised concerns about the recycling and disposal methods for EV batteries. Unlike traditional internal combustion engine vehicles, EVs require unique and safe methods for the recovery and disposal of their batteries. In this process, predicting the lifespan of the battery is essential. Impedance and State of Charge (SOC) analysis are commonly used methods for this purpose. However, predicting the lifespan of batteries with complex chemical characteristics through electrical measurements presents significant challenges. To enhance the accuracy and precision of existing measurement methods, this paper proposes using a Long Short-Term Memory (LSTM) model, a type of deep learning-based recurrent neural network, to diagnose battery performance. The goal is to achieve safe classification through this model. The designed structure was evaluated, yielding results with a Mean Absolute Error (MAE) of 0.8451, a Root Mean Square Error (RMSE) of 1.3448, and an accuracy of 0.984, demonstrating excellent performance.

• Journal of the Korean Institute of Gas
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• v.23 no.1
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• pp.54-61
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• 2019

As the market for portable electronic devices expands, the demand for Lithium Ion Battery (LIB) is also increasing. LIB has higher efficiency than other secondary batteries, but there is a risk of explosion / fire due to thermal runaway reaction. Especially, Electric Vehicles (EV) equipped with a large capacity LIB cell also has a danger due to a large amount of toxic gas generated by a fire. Therefore, it is necessary to analyze the risk of toxic gas generated by EV fire to minimize accident damage. In this study, the flow of toxic gas generated by EV fire was numerically analyzed using Computational Fluid Dynamic. Scenarios were established based on literature data and EV data to confirm the effect distance according to time and exposure standard. The purpose of this study is to analyze the risk of toxic gas caused by EV fire and to help minimize the loss of life and property caused by accidents.

• Resources Recycling
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• v.31 no.4
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• pp.3-11
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• 2022

Owing to the increasing demand for electric vehicles (EVs), appropriate management of their waste batteries is required urgently for scrapped vehicles or for addressing battery aging. With respect to technological developments, data-driven diagnosis of waste EV batteries and management technologies have drawn increasing attention. Moreover, robot-based automatic dismantling technologies, which are seemingly interesting, require industrial verifications and linkages with future battery-related database systems. Among these, it is critical to develop and disseminate various advanced battery diagnosis and assessment techniques to improve the efficiency and safety/environment of the recirculation of waste batteries. Incorporation of lithium-related chemical substances in the public pollutant release and transfer register (PRTR) database as well as in-depth risk assessment of gas emissions in waste EV battery combustion and their relevant fire safety are some of the necessary steps. Further research and development thus are needed for optimizing the lifecycle management of waste batteries from various aspects related to data-based diagnosis/classification/disassembly processes as well as reuse/recycling and final disposal. The idea here is that the data should contribute to clean design and manufacturing to reduce the environmental burden and facilitate reuse/recycling in future production of EV batteries. Such optimization should also consider the future technological and market trends.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.4
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• pp.95-104
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• 2013

As global warming and depletion of fossil fuel are considered as urgent problems, the development of electric vehicle (EV) is getting more attention by automobile industry. However, the wide adoption of EVs is not coming yet, because of many issues such as long recharging time and high cost of batteries etc. As an alternative solution to the conventional battery charging EV, the idea of battery exchanging EV is introduced. To realize the battery exchanging business model, one should solve the issues of ownership and reliability of battery. To address such issues, the concept of battery sharing should be considered together with good traceability system. In this study, we studied RFID code structure to provide better visibility and traceability for shared EV batteries. The proposed RFID code and code generation system is based on GRAI-96 of EPCglobal and included factors such as chemical, physical, and manufacturing features. The designed code can be also used as the ID of each battery.