• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.355-358
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• 1996

Electrical Power System (EPS) of Electric Vehicle which consists of batteries, motor and driving subsystem, has been modeled. A battery model is modeled with an electrical circuit representing a characteristics of real battery. Driving subsystem is modeled as three different level namely exact, average and functional models. Load profile includes road information, speed profile and EV mechanical parameters, which are incorporated into a reference torque in the driving subsystem model. A system model is integrated to simulate the performance of electric vehicle such as energy balance, battery status, and electrical stress of each subsystem.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.4
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• pp.316-324
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• 2022

This paper uses seasonal auto-regressive integrated moving average (S-ARIMA), which is efficient in seasonality between time-series models, to predict the degradation tendency for lithium-ion batteries and study a method for improving the predictive performance. The proposed method analyzes the degradation tendency and extracted factors through an electrical characteristic experiment of lithium-ion batteries, and verifies whether time-series data are suitable for the S-ARIMA model through several statistical analysis techniques. Finally, prediction of battery aging is performed through S-ARIMA, and performance of the model is verified through error comparison of predictions through mean absolute error.

• Transactions of Materials Processing
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• v.32 no.3
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• pp.136-144
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• 2023

This study analyzed the mechanical behavior of lithium-ion battery pouch material and predicted its formability. A homogenization method was used to evaluate the physical properties of the pouch, and a new hardening model was developed. The yield function for the plastic model was optimized, and the anisotropic property was determined. Also, the forming limits were measured and predicted using the M-K forming limit diagram. Finally, a square cup drawing experiment confirmed the accuracy of the measured mechanical properties and the formability calculation.

• 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.5 no.5
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• pp.435-442
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• 2000

Started upon Its discovery by Wright et al in 1773, studies on the solid polymer electrolyte are being carried out vigorously. So, models of Li-polymer battery have been developed through R-L-C components combination and PSpice functional block in this parer. The impedance characteristics of Li-polymer battery with R-L-C components are presented. Simulation results using PSpice functional model are compared with measured charge/discharge characteristics. Also, as to the number of cycle(charge/discharge), coulomb efficiency of Li-polymer is evaluated through experimental results.

• 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.

• Journal of Power Electronics
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• v.15 no.4
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• pp.1006-1017
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• 2015

This paper presents a finite control set model predictive control (FCS-MPC) strategy for the AC/DC matrix converter used in grid-connected battery energy storage system (BESS). First, to control the grid current properly, the DC current is also included in the cost function because of input and output direct coupling. The DC current reference is generated based on the dynamic relationship of the two currents, so the grid current gains improved transient state performance. Furthermore, the steady state error is reduced by adding a closed-loop. Second, a Luenberger observer is adopted to detect the AC input voltage instead of sensors, so the cost is reduced and the reliability can be enhanced. Third, a switching state pre-selection method that only needs to evaluate half of the active switching states is presented, with the advantages of shorter calculation time, no high dv/dt at the DC terminal, and less switching loss. The robustness under grid voltage distortion and parameter sensibility are discussed as well. Simulation and experimental results confirm the good performance of the proposed scheme for battery charging and discharging control.

• Journal of Drive and Control
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• v.16 no.1
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• pp.45-53
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• 2019

The objective of this study was to design and model the PEM fuel cell excavator with supercapacitor/battery hybrid power source to increase efficiency as well as eliminate greenhouse gas emission. With this configuration, the system can get rid of the internal combustion engine, which has a low efficiency and high emission. For the analysis and simulation, the governing equations of the PEM system, the supercapacitor and battery were derived. These simulations were performed in MATLAB/Simulink environment. The hydraulic modeling of the excavator was also presented, and its model implemented in AMESim and studied. The whole system model was built in a co-simulation environment, which is a combination of MATLAB/Simulink and AMESim software. The simulation results were presented to show the performance of the system.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.6
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• pp.381-389
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• 2021

Most diagnosis approaches rely on historical failure data that might not be feasible in real operating conditions because the battery voltage and internal parameters are nonlinear according to various operating conditions, such as cell-to-cell configuration and initial condition. To overcome this issue, the estimator and the predictor require integrated approaches that consider comprehensive data, with the degradation process and measured data taken into account. In this paper, vector autoregressive models (VAR) with various parameters that affect overdischarge to the cell in the battery pack were constructed, and the cell-to-cell parameters were identified using an adaptive model to analyze the influence of failure prognosis. The theoretical analysis is validated using experimental results in terms of the feasibility and advantages of fault prognosis.

• Korean Chemical Engineering Research
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• v.60 no.3
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• pp.363-370
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• 2022

In this paper, an estimation algorithm for state of charge (SOC) was applied using an equivalent circuit model (ECM) and an Extended Kalman Filter (EKF) to improve the estimation accuracy of the battery system states. In particular, an observer was designed to estimate SOC along with the aged capacity. In the case of the fresh battery, when SOC was estimated by Kalman Filter (KF), the mean absolute percentage error (MAPE) was 0.27% which was smaller than MAPE of 1.43% when the SOC was calculated by the model without the observer. In the driving mode of the vehicle, the general KF or EKF algorithm cannot be used to estimate both SOC and capacity. Considering that the battery aging does not occur in a short period of time, a strategy of periodically estimating the battery capacity during charging was proposed. In the charging mode, since the current is fixed at some intervals, a strategy for estimating the capacity along with the SOC in this situation was suggested. When the current was fixed, MAPE of SOC estimation was 0.54%, and the MAPE of capacity estimation was 2.24%. Since the current is fixed when charging, it is feasible to estimate the battery capacity and SOC simultaneously using the general EKF. This method can be used to periodically perform battery capacity correction when charging the battery. When driving, the SOC can be estimated using EKF with the corrected capacity.