• Journal of Power Electronics
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• v.17 no.2
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• pp.398-410
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• 2017

This work presents the design of a dual extended Kalman filter (EKF) as a state/parameter estimator suitable for adaptive state-of-charge (SoC) estimation of an automotive lithium-iron-phosphate ($LiFePO_4$) cell. The design of both estimators is based on an experimentally identified, lumped-parameter equivalent battery electrical circuit model. In the proposed estimation scheme, the parameter estimator has been used to adapt the SoC EKF-based estimator, which may be sensitive to nonlinear map errors of battery parameters. A suitable weighting scheme has also been proposed to achieve a smooth transition between the parameter estimator-based adaptation and internal model within the SoC estimator. The effectiveness of the proposed SoC and parameter estimators, as well as the combined dual estimator, has been verified through computer simulations on the developed battery model subject to New European Driving Cycle (NEDC) related operating regimes.

• Journal of Electrical Engineering and Technology
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• v.8 no.4
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• pp.787-798
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• 2013

This paper proposes a special power circuit topology and its corresponding control strategy for an energy recovery power accumulator battery pack testing system (PABPTS), which is particularly used in electric vehicles. Firstly, operation principle and related parameter design for the system are illustrated. Secondly, control strategy of the composite power converter for PABPTS is analyzed in detail. The improved scheme includes a high accuracy charge and discharge current closed loop. active power reference for the grid-side inverter is provided by the result of multiplication between battery pack terminal voltage and test current. Simulation and experimental results demonstrate that the proposed scheme could not only satisfy the requirements for PABPTS with wide-range current test, but also could recover the discharging energy to the power grid with high efficiency.

• Journal of Power Electronics
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• v.16 no.3
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• pp.1131-1140
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• 2016

A simple design for a sliding mode observer is proposed for EV lithium battery SOC estimation in this paper. The proposed observer does not have the limiting conditions of existing observers. Compared to the design of previous sliding mode observers, the new observer does not require a solving matrix equation and it does not need many observers for all of the state components. As a result, it is simple in terms of calculations and convenient for engineering applications. The new observer is suitable for both time-variant and time-invariant models of battery SOC estimation, and the robustness of the new observer is proved by Liapunov stability theorem. Battery tests are performed with simulated FUDS cycles. The proposed observer is used for the SOC estimation on both unchanging parameter and changing parameter models. The estimation results show that the new observer is robust and that the estimation precision can be improved base on a more accurate battery model.

• Transactions on Electrical and Electronic Materials
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• v.17 no.6
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• pp.311-316
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• 2016

Batteries are critical components of electric vehicles and energy storage systems. The connection of a battery to the power grid for charge and discharge greatly affects energy storage. Therefore, an accurate and easy-to-observe battery model should be established to achieve systematic design, simulation, and SOC (state of charge) estimations. In this review, several equivalent circuit models of representative significance are explained, and their respective advantages and disadvantages are compared to determine and outline their reasonable applications to Li-ion batteries. Numerous commonly used model parameter identification principles are summarized as well, and basic model verification methods are briefly introduced for the convenient use of such models.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.9
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• pp.1714-1719
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• 2009

In this paper, methodology of battery optimal designing is proposed. Fuel cell model including dynamic characteristic is developed and load model is produced by considering driving schedule. Using these models, required energy of load and supplying energy from fuel cell are analyzed by comparing simulation results. Also parameter of fuel cell model is changed variously and battery capacity is calculated in each cases. And methode of battery optimal designing is presented by regarding dynamic characteristic of fuel cell.

• Journal of Aerospace System Engineering
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• v.14 no.6
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• pp.74-78
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• 2020

The cooler driver electronics (CDE) for maintaining a low temperature of a satellite payload IR sensor has a compressor with a pulsation current load when in operation. This pulsation current creates a large voltage fluctuation and may negatively affect both the load and regulated bus stability. Thus, a CDE power conditioning system has a battery for use as a buffer that is connected in front of the CDE load line. In this system, a battery charger limiter circuit is required to protect from an over-charge of the battery and power to the load. In this study, an optimal design and parameter selection were developed and simulated.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2008.10a
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• pp.249-252
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• 2008

Micro V-notching process has been used to manufacturing the safety component in Li-Ion battery. These kinds of safety component in Li-Ion battery plays an important role in the explosion from excessive overheating. Therefore, it is very crucial to estimate accurately the working pressure range of the safety component with micro V-notch. In this study, the relationship with the working internal pressure in Li-Ion battery and fracture phenomenon in micro V-notch was investigated through the numerical analysis. The numerical analysis is especially adopted the finite element method with ductile fracture criteria.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.5
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• pp.360-368
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• 2008

A lumped parameter model of Li-ion battery in hybrid electric vehicle(HEV) is constructed and system parameters are identified by using recursive least square estimation for different C-rates, SOCs and temperatures. The system characteristics of pole and zero in the frequency domain are analyzed with the parameters obtained from different conditions. The parameterized model of a Li-ion battery indicates highly dependent of temperatures. To estimate SOC and polarization voltage, a Luenberger state observer is utilized. The P- or PI-gains of observer based on a suitable natural frequency and damping ratio is adopted for the state estimation. Satisfactory estimation accuracy of output voltage and SOC is especially obtained by a PI-gain. The feasibility of the proposed estimation method is verified through experiment under the conditions of different C-rates, SOCs and temperatures.

• Journal of Information Processing Systems
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• v.12 no.3
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• pp.436-454
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• 2016

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected based on the HTC One X hardware platform. We considered various setting factors, such as Bluetooth, brightness, 3G, GPS, Wi-Fi, and Sync. The battery levels for each possible state vector were measured, and then we constructed the battery prediction model using different regression functions based on the collected data. The accuracy of the constructed models using the multi-layer perceptron (MLP) and the support vector machine (SVM) were compared using varying kernel functions. Various parameters for MLP and SVM were considered. The measurement of prediction efficiency was done by the mean absolute error (MAE) and the root mean squared error (RMSE). The experiments showed that the MLP with linear regression performs well overall, while the SVM with the polynomial kernel function based on the linear regression gives a low MAE and RMSE. As a result, we were able to demonstrate how to apply the derived model to predict the remaining battery charge.

• Journal of Power Electronics
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• v.15 no.6
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• pp.1446-1455
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• 2015

This paper illustrates resonant tank design considerations and the implementation of a LLC resonant converter with a wide battery voltage range based on the fundamental harmonic approximation (FHA) analysis. Unlike the conventional design at zero load, the parameter K (the ratio of the transformer magnetizing inductor L_m to the resonant inductor L_r) of the LLC converter in this paper is designed with two charging points, (V_{o_min}, I_{o_max1}) and (V_{o_max}, I_{o_max2}), according to the battery charging strategy. A 2.9kW prototype with an output voltage range of 36V to 72V dc is built to verify the design. It achieves a peak efficiency of 96%.