• Journal of IKEEE
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• v.26 no.4
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• pp.531-536
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• 2022

In order to efficeintly manage a battery, it is important to accurately estimate and manage the SOH(State of Health) and RUL(Remaining Useful Life) of the batteries. Even if the batteries are of the same type, the characteristics such as facility capacity and voltage are different, and when the battery for the training model and the battery for prediction through the model are different, there is a limit to measuring the accuracy. In this paper, We proposed the entropy index using voltage distribution and discharge time is generalized, and four batteries are defined as a training set and a test set alternately one by one to predict the health status of batteries through linear regression analysis of machine learning. The proposed method showed a high accuracy of more than 95% using the MAPE(Mean Absolute Percentage Error).

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.2
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• pp.175-181
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• 2015

In this study, a lithium polymer battery (LiPB) is simply expressed by a primary RC equivalent model. The PI state observer is designed in Matlab/Simulink. The non-linear relationship with the OCV-SOC is represented to be linearized with 0.1 pu intervals by using battery parameters obtained by constant-current pulse discharge. A state equation is configured based on battery parameters. The state equation, which applied Peukert's law, can estimate SOC more accurately. SOC estimation capability was analyzed by utilizing reduced Federal Test Procedure (FTP-72) current profile and using a bi-directional DC-DC converter at temperature ($25^{\circ}C$). The PI state observer, which is designed in this study, indicated a SOC estimation error rate of ${\pm}2%$ in any of the initial SOC states. The PI state observer confirms a strong SOC estimation performance despite disturbances, such as modeling errors and noise.

• The Transactions of the Korean Institute of Power Electronics
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• v.19 no.2
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• pp.139-148
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• 2014

State-of-charge (SOC) is one of the significant indicators to estimate the driving range of the electric vehicle and to control the alternator of the conventional engine vehicles as well. Therefore its precise estimation is crucial not only for utilizing the energy effectively but also preventing critical situations happening to the power train and lengthening the lifetime of the battery. However, lead-acid battery is time-variant, highly nonlinear, and the hysteresis phenomenon causes large errors in estimation SOC of the battery especially under the frequent discharge/charge. This paper proposes a novel estimation technique for the SOC of the Lead-Acid battery by using a well-known Extended Kalman Filter (EKF) and an electrical equivalent circuit model of the Lead-Acid battery considering diffusion and hysteresis characteristics. The diffusion is considered by the reconstruction of the open circuit voltage decay depending on the rest time and the hysteresis effect is modeled by calculating the normalized integration of the charge throughput during the partial cycle. The validity of the proposed algorithm is verified through the experiments.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.560-562
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• 1998

A new approach to developing battery SOC indicator for electric vehicle is discussed in this paper. One of the most difficult problems associated with the development of electric vehicle is the battery indicator which reliably informs the state of charge(SOC) of the battery to the driver. And the condition to be satisfied with SOC indicator installed on the electric vehicle is that it should be used under frequently variable load. A new method to determining SOC using neural networks(NN) is proposed to satify the condition. The training data of NN are obtained by using mathematical model of lead-acid battery, and calculating discharge currents and terminal voltages while battery discharges with constant current. The 3-layered NN with back propagation algorithm is used Simulation results show that the proposed method is appropriate as SOC indicator of the battery.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.12
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• pp.74-83
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• 2014

This paper proposes a study on the configuration of balancing of plant(BOP) and implementation of battery management system(BMS) functions for vanadium redox flow battery(VRFB) and propose a method consists of sensor and required design specifications BOP system configuration. And it proposes an method of the functions implementation and control algorithm of the BMS for flow battery. Functions of BMS include temperature control, the charge and discharge control, flow control, level control, state of charge(SOC) estimation and a battery protection through the sensor signal of BOP. Functions of BMS is implemented by the sensor signal, so it is recognized as a very important factor measurement accuracy of the data. Therefore, measuring a mechanical signal(flow rate, temperature, level) through the BOP test model, and the measuring an electrical signal(cell voltage, stack voltage and stack current) through the VRFB charge-discharge system and analyzes the precision of data in this paper. Also it shows a good charge-discharge test results by the SOC estimation algorithm of VRFB. Proposed BOP configuration and BMS functions implementation can be used as a reference indicator for VRFB system design.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.5
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• pp.694-702
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• 2014

One of the most important devices in an underwater vessel is a propulsion system. It should be a quiet and efficient system for stealthy operations in the large mission area. Hence lead-acid battery system has been used to supply the energy to electric motor. Recent technological developments and improvements, such as polymer electrolyte membrane(PEM) fuel cell and lithium polymer battery and have created the potential to improve overall power and propulsion performance. An underwater vessel always starts their mission with a limited energy and is not easy to refuel. Therefore design of energy elements, such as fuel cell and battery, and their load distribution are important to increase the maximum operating time of underwater vessel. In this paper, the lead-acid battery/PEM fuel cell and lithium polymer battery/PEM fuel cell were suggested as propulsion system and their performances were analyzed by modeling and simulation using Matlab/Simulink. Each model concentrated on representing the characteristics of energy element depending on demand current. As a result the effect of load distribution between battery and fuel cell was evaluated and the operation time of each propulsion system was able to be estimated exactly.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.3
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• pp.63-72
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• 2014

The exchangeable battery electric bus is an eco-friendly public transportation vehicle. Due to the technological limitation, however, it should repeatedly change batteries with charged ones. The unmanned battery exchangeable electric bus being studied in Korea can exchange batteries automatically by using a battery swapping system. In this paper, we propose an unmanned battery exchangeable electric bus management system. The proposed system provides two services: the bus information service and the battery change scheduling service. The bus information service is the existing traditional metropolitan area bus information systems, which inform bus passengers how long they should wait for the buses. Our second service assigns a low-battery bus, which needs to change the batteries, to the battery swapping system, which stores fully-charged batteries. To validate the proposed system, we model the system by using the DEVS formalism. The simulation result shows that the proposed system provides the services properly.

• Journal of Convergence Society for SMB
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• v.5 no.2
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• pp.15-20
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• 2015

Recently, as smart phone technology is developing, wearable devices is also accelerating. But, the wearable device is necessary to operated for a long time with a small electric power because werable device is made compact. In this paper, we design and implement efficient lithium polymer battery model suitable to miniaturized wearable device in oder to maximize ease of use. The proposed model is characterized by a compact size of the battery by applying a thermal element and a light-weight battery. Also, proposed model gives greatly improve the life of wearable devices because it uses a method using the characteristics of the Peltier device using the temperature difference between the room temperature and body temperature of a person to generate power for charging. In particular, the proposed model can be used for the wearable device, as well as auxiliary charging of the smart phone.

• Design & Manufacturing
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• v.16 no.1
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• pp.36-42
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• 2022

Globally, as population growth and economic development continue, resource consumption is increasing rapidly. As an alternative to electric vehicles was suggested as the environmental pollution problem emerged, the number of registered electric vehicles in Korea increased by more than 137 times compared to 2013. Secondary batteries are expected to expand into various markets such as small IT devices and electric vehicles, and the most important part of electric vehicles is the battery (secondary battery). Therefore, in this study, to analyze the stability of the CSM (Classifier Separator Mill) grinding disc that crushes secondary battery raw materials, structural analysis and vibration analysis of the 1st to 4th grinding discs and the final model were performed. The change of bending by the weight of the Grinding Disc is at least 0.065㎛ and maximum 0.075㎛, and the change by the standard gravity is judged to be very low. The strain is at least 0.00031㎛/㎛ and maximum 0.00078㎛/㎛, and even if the number of Hamer increases, the change by the weight is judged to be insignificant. When the Grinding Disc rotates at a maximum of 6000rpm, the deformation and deformation rate of the first to third models are similar, but the fourth model (Hamer 10EA) is more than three times and the final model (Hamer 12EA) is about four times. However, the maximum deformation is 28.21㎛, which is considered to be insignificant when the change is 6000rpm. Six modes of natural Frequency analysis of the 1st~4th order and final model of the grinding disc appeared to be bent or twisted.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.5
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• pp.22-28
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• 2017

The performance of lithium ion batteries used in electric vehicles (EV) varies greatly depending on the battery temperature. In this paper, the finite difference method was used to evaluate the temperature change, state of charge (SOC), internal resistance, and voltage change of the battery due to heat generation in the battery. The simulation model was linked with AMESim to calculate the driving range of an EV traveling in New European Driving Cycle (NEDC) mode. As the temperature dropped below $25^{\circ}C$, the internal resistance of the battery increased, which increased the amount of heat generated and decreased the driving range of EV. At battery temperatures above $25^{\circ}C$, the driving range was also decreased due to reduced SOC that deteriorated the battery performance. The battery showed optimal performance and the driving range was maximized at $25^{\circ}C$. When battery temperatures of $-20^{\circ}C$ and $45^{\circ}C$, the driving range of EV decreased by 33% and 1.8%, respectively. Maintaining the optimum battery temperature requires heating the battery at low temperature and cooling it down at high temperature through efficient battery thermal management. Approximately 500 W of heat should be supplied to the battery when the ambient temperature is $-20^{\circ}C$, while 250 W of heat should be removed for the battery to be maintained at $25^{\circ}C$.