• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1085-1091
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• 2014

A model based SOC estimation scheme using parameter identification is described and applied to a Lithium-ion battery module that can be installed in electric vehicles. Simulation studies are performed to verify the effect of sensor faults on the SOC estimation results for terminal voltage sensor and load current sensor. The sensor faults should be detected and isolated as soon as possible because the SOC estimation error due to any sensor fault seriously affects the overall performance of the BMS. A new fault detection and isolation(FDI) scheme by which the fault of terminal voltage sensor and load current sensor can be detected and isolated is proposed to improve the reliability of the BMS. The proposed FDI scheme utilizes the parameter estimation of an input-output model and two fuzzy predictors for residual generation; one for terminal voltage and the other for load current. Recently developed dual polarization(DP) model is taken to develope and evaluate the performance of the proposed FDI scheme. Simulation results show the practical feasibility of the proposed FDI scheme.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.4
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• pp.303-310
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• 2020

Estimating the accurate internal state of lithium ion batteries to increase their safety and efficiency is crucial. Various algorithms are used to estimate the internal state of a lithium ion battery, such as the extended Kalman filter and sliding mode observer. A state-space model is essential in using algorithms to estimate the internal state of a battery. Two principal methods are used to express the state-space model, namely, continuous time and discrete time. In this work, the extended Kalman filter is employed to estimate the internal state of a battery. Moreover, this work presents and analyzes the estimation performance of algorithms consisting of a continuous time state-space model and a discrete time state-space model through static and dynamic profiles.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.5
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• pp.623-628
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• 2006

Laser material processing is a very fast advancing technology for various industrial applications. because of many advantages. Its major advantage of less and controlled heat input has been exploited successfully for the very critical application of aluminium alloy welding. This study suggested the occurrence source of weld-defects and its solution methods in a welding of lithium ion battery by pulsed Nd:YAG laser. In experiment. battery case has changed over joint geometry from welding of side position to flat one. In the case of a electrolyte injection hole in order to seal it. welding is carried out after pressing Al ball. At this time. an eccentric degree. contact length and gap are worked as a major parameters. As improving the method of Al ball pressing. it was able to reduce an eccentricity. increase the contact length and decrease gap. As a results of a experiment. a sound weld bead shape and crack-free weld bead can be obtained.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.339-343
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• 2005

Laser material processing is a very fast growing technology for various industrial applications, because of many advantages. Its major advantage of less and controlled heat input has been exploited successfully for the very critical application of aluminium alloy welding. This study suggested the occurrence source of weld-defects and its solution methods in a welding of lithium ion battery by pulsed Nd:YAG laser. In experiment, battery case has changed over joint geometry from welding of side position to flat one. In case of a electrolyte injection hole in order to seal it, welding is carried out after pressing Al ball. At this time, an eccentric degree, contact length and gap are worked as a major parameters. As improving the method of Al ball pressing, it was able to reduce an eccentricity, increase the contact length and decrease gap. As a results of a experiment, a sound weld bead shape and crack-free weld bead can be obtained.

• Journal of Power Electronics
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• v.17 no.5
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• pp.1288-1297
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• 2017

The estimation of the remaining useful life (RUL) of lithium-ion (Li-ion) batteries is important for intelligent battery management system (BMS). Data mining technology is becoming increasingly mature, and the RUL estimation of Li-ion batteries based on data-driven prognostics is more accurate with the arrival of the era of big data. However, the support vector machine (SVM), which is applied to predict the RUL of Li-ion batteries, uses the traditional single-radial basis kernel function. This type of classifier has weak generalization ability, and it easily shows the problem of data migration, which results in inaccurate prediction of the RUL of Li-ion batteries. In this study, a novel multi-kernel SVM (MSVM) based on polynomial kernel and radial basis kernel function is proposed. Moreover, the particle swarm optimization algorithm is used to search the kernel parameters, penalty factor, and weight coefficient of the MSVM model. Finally, this paper utilizes the NASA battery dataset to form the observed data sequence for regression prediction. Results show that the improved algorithm not only has better prediction accuracy and stronger generalization ability but also decreases training time and computational complexity.

• Journal of the Semiconductor & Display Technology
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• v.7 no.2
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• pp.13-17
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• 2008

In this paper, in order to get the characteristics of the lithium secondary cell, such as charge and discharge characteristic, temperature characteristic, self-discharge characteristic and the capacity recovery rate etc, we build a thermal model that estimate the impedance of battery by experiment & simulation. In this one-dimensional model, Seven governing equations are made to solve seven variables c, $c_s,\;\Phi_1,\;\Phi_2,\;i_2$, j and T. The thermal model parameters used in this model have been adjusted according to the experimental data measured in the laboratory. The result(Voc, Impedance) of this research can be used in BMS(Battery Management System), so an efficient method of using battery is developed.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.3
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• pp.300-304
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• 2012

This paper presents a nonlinear observer design method for SOC(state-of-charge) estimation of Lithium polymer battery cell. The dynamic equation of the battery cell is modeled as a simple RC electrical circuit with a nonlinear voltage source and the parameters are obtained via nonlinear optimization. Using the sum of squares decomposition, the observer gain is designed such that the error dynamics is asymptotically stable and the decay rate is below the prescribed value. In order to illustrate the performance of the observer, a computer simulation is performed using the experimental data with the UDDS(urban dynamometer driving schedule) current profile.

• Journal of Power Electronics
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• v.12 no.5
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• pp.778-786
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• 2012

In this paper, a novel scheme for the condition monitoring of lithium polymer batteries is proposed, based on the sigma-point Kalman filter (SPKF) theory. For this, a runtime-based battery model is derived, from which the state-of-charge (SOC) and the capacity of the battery are accurately predicted. By considering the variation of the serial ohmic resistance ($R_o$) in this model, the estimation performance is improved. Furthermore, with the SPKF, the effects of the sensing noise and disturbance can be compensated and the estimation error due to linearization of the nonlinear battery model is decreased. The effectiveness of the proposed method is verified by Matlab/Simulink simulation and experimental results. The results have shown that in the range of a SOC that is higher than 40%, the estimation error is about 1.2% in the simulation and 1.5% in the experiment. In addition, the convergence time in the SPKF algorithm can be as fast as 300 s.

• The Transactions of the Korean Institute of Power Electronics
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• v.12 no.4
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• pp.324-331
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• 2007

This paper studies new estimation method for state of charge (SOC) of the hybrid electric vehicle lithium battery using sliding mode observer. A simple R-C Lithium battery modeling technique is established and the errors caused by simple modeling was compensated by the sliding mode observer. The structure of the sliding mode observer is simple, but it shows robust control property against modeling errors and uncertainties. The performance of the system has been verified by the UUDS test. The test results of the proposed observer system shows robust tracking performance under real driving environments.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.13-15
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• 2008

Charging or discharging secondary batteries such as a lithium-ion battery is essential in the stage of production and takes long time over two hours. And the charge/discharge system is operated with high switching frequency over several tens kHz. Therefore, to simulate such a system in the conventional way takes very long time and huge files are produced. Finally, the simulation would be unable with general PC class. In this paper, the lithium-ion battery charge/discharge system is analyzed by using state space averaging method. As a result, the simulation time is reduced dramatically and the charge/- discharge characteristics of the lithium-ion battery can be observed.