• Journal of Power Electronics
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• v.14 no.5
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• pp.1038-1046
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• 2014

Lithium-ion batteries are widely used in hybrid and pure electric vehicles. State-of-charge (SOC) estimation is a fundamental issue in vehicle power train control and battery management systems. This study proposes a novel model-based SOC estimation method that applies closed-loop state observer theory and a comprehensive battery model. The state-space model of lithium-ion battery is developed based on a three-order resistor-capacitor equivalent circuit model. The least square algorithm is used to identify model parameters. A multi-state closed-loop state observer is designed to predict the open-circuit voltage (OCV) of a battery based on the battery state-space model. Battery SOC can then be estimated based on the corresponding relationship between battery OCV and SOC. Finally, practical driving tests that use two types of typical driving cycle are performed to verify the proposed SOC estimation method. Test results prove that the proposed estimation method is reasonably accurate and exhibits accuracy in estimating SOC within 2% under different driving cycles.

• Journal of Power Electronics
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• v.12 no.1
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• pp.1-9
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• 2012

This study investigates an application of the Hamming network-dual extended Kalman filter (DEKF) based on pattern recognition for high accuracy state-of-charge (SOC)/capacity estimation and state-of-health (SOH) prediction at various temperatures. The averaged nine discharging/charging voltage-temperature (DCVT) patterns for ten fresh Li-Ion cells at experimental temperatures are measured as representative patterns, together with cell model parameters. Through statistical analysis, the Hamming network is applied to identify the representative pattern that matches most closely with the pattern of an arbitrary cell measured at any temperature. Based on temperature-checking process, model parameters for a representative DCVT pattern can then be applied to estimate SOC/capacity and to predict SOH of an arbitrary cell using the DEKF. This avoids the need for repeated parameter measuremet.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.1
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• pp.27-32
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• 2011

These days more electric devices are implemented in car, and more accurate estimation of SoC is required. OCV with current integration and Internal Resistance is essential method of Battery SoC Estimation. In this paper we propose OCV with current integration method and compare with Internal Resistance method. In OCV with current integration method estimation error was less than average 2%, but requires more than 5 minutes to stabilize OCV. If Stop and Running conditions are change frequently, estimation error will increase. In Internal resistance Modeling method, in high SoC state, estimation error was more than 15%, and in low SoC state, estimation error was less than 8%.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2412-2420
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• 2018

The thermal degradation of low density polyethylene (LDPE) will accelerate the production of carbonyl groups (C=O), which can act as the induced dipoles under high voltage. In this paper, we researched the dielectric properties and space charge behavior of LDPE after thermal aging, which can help us to understand the correlation between carbonyl groups (C=O) and electrical properties of LDPE. The spectra results show that LDPE exhibit obvious thermooxidative reactions when the aging time is 35 days and the productions mainly contain carboxylic acid, carboxylic eater and carboxylic anhydride, whose amount increase with the increasing of aging time. The dielectric properties show that the real permittivity of LDPE is inversely proportional to temperature before aging and subsequently become proportional to temperature after thermal aging. Furthermore, both the real and imaginary permittivity increase sharply with the increasing of aging time. The fitting results of imaginary permittivity show that DC conductivity become more sensitive about temperature after thermal aging. On this basis, the active energies of materials calculated from DC conductivity increase first and then decrease with the increasing of aging time. In addition, the space charge results show that the heterocharges accumulated near electrodes in LDPE change to the homocharges after thermal aging and the mean volume charge density increase with the increasing of aging time. It is considered that the overlaps caused by electrical potential area is the main reason for the increase of DC conductivity.

• The Journal of Korean Institute of Information Technology
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• v.18 no.5
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• pp.55-64
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• 2020

Estimating the state of charge (SOC) of a battery is essential for increasing the stability and reliability of a photovoltaic system. In this study, battery SOC estimation methods were proposed using artificial neural networks (ANNs) with gradient descent (GD), Levenberg-Marquardt (LM), and scaled conjugate gradient (SCG), and an adaptive neuro-fuzzy inference system (ANFIS). The charge start voltage and the integrated charge current were used as input data and the SOC was used as output data. Four models (ANN-GD, ANN-LM, ANN-SCG, and ANFIS) were implemented for battery SOC estimation and compared using MATLAB. The experimental results revealed that battery SOC estimation using the ANFIS model had both the highest accuracy and highest convergence speed.

• Proceedings of KOSOMES biannual meeting
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• 2000.05a
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• pp.86-100
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• 2000

The author of this document is generally in charge of Port State Control affairs at the headquarters of Ministry of Transport, Japan. In this document, the necessity of Port State Control, the brief history of japanese Port State Control and the present system of Port State Control in Japan are introduced. Also, the newest output of Japanese Port State Control which is an annual statistic of 1999 is explained, subsequently the policy and strategy on Port State Control in Japan is introduced.

• Proceedings of the Korean Fiber Society Conference
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• 2007.11a
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• pp.10-12
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• 2007

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• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.4
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• pp.28-35
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• 2007

In this paper, a study was made of the technology used to measure the remaining amount of energy in secondary cells, for which demand is ever increasing. First, the standard data were stored for measurement of the remaining energy and a compare/analysis algorithm was developed. Next, hardware was designed and a prototype that can display the SOC(State Of Charge) through an LCD displayinstrument was created. The small size of the prototype allows it to be portable and its performance is within ${\pm}4$[%].

• Journal of Power Electronics
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• v.16 no.1
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• pp.238-248
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• 2016

The state-of-charge (SOC) and state-of-health (SOH) estimation of batteries play important roles in managing batteries for automotive applications. However, an accurate state estimation of a battery is difficult to achieve because of certain factors, such as measurement noise, highly nonlinear characteristics, strong hysteresis phenomenon, and diffusion effect of batteries. In certain vehicular applications, such as idle stop-start systems (ISSs), significant errors in SOC/SOH estimation may lead to a failure in restarting a combustion engine after the shut-off period of the engine when the vehicle is at rest, such as at a traffic light. In this paper, a dual extended Kalman filter algorithm with a dynamic equivalent circuit model of a lead-acid battery is proposed to deal with this problem. The proposed algorithm adopts a battery model by taking into account the hysteresis phenomenon, diffusion effect, and parameter variations for accurate state estimations of the battery. The validity of the proposed algorithm is verified through experiments by using an absorbed glass mat valve-regulated lead-acid battery and a battery sensor cable for commercial ISS vehicles.

• Journal of the Korean Magnetic Resonance Society
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• v.22 no.4
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• pp.101-106
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• 2018

Magnetite is the oldest magnet material known to mankind. It is getting attention again from solid state physics researchers now a days because it is one of the most strongly correlated electron systems. Spin, charge, and orbital orders are interplaying with lattice and involved in the Verwey transition where magnetization, conductivity, and structure changes suddenly. The peculiar ordering states above and below the transition temperature mainly originate from the coexistence of $Fe^{2+}$ and $Fe^{3+}$ ions in the B site of the inverse spinel structure. In particular, the state of the charge and orbital order was the oldest and most intriguing problem. NMR has made significant contribution to the investigation of this question. A. Abragam stated that there is no doubt that NMR is a very powerful tool for the study of ferromagnetic and antiferromagnetic materials. In this mini-review, a short history of NMR investigation of magnetite is presented, providing a support to Abragam's claim.