• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.217-222
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• 2018

The deterioration of the Battery is decided by SoC and SoH. To determine Battery deterioration, SoC measurement method of Battery by Transfer Function was studied. The SoC of the Battery changes most greatly in the 1Hz band where the DC resistance is detected. but it is a narrow band to observe, therefore, the observation band was moved to 1kHz using the tone busrst signal. Welch's method was used to observe the frequency domain characteristics of the signal. As a result of the spectral estimation, it was confirmed that the response signal of the battery is 1dB difference when the SoC is 40%, 60%, and 80%, respectively. Through this, Proposed the new method of Battery SoC measurement.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.2
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• pp.85-92
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• 2022

Currently, various researches on electric vehicle battery systems have been conducted from the viewpoint of safety and performance for SoC, SoH, etc. However, it is difficult to build a precise electrical model of a battery system based on the chemical reaction and SoC prediction. Experimental measurements and predictions of the battery SoC were usually performed using dynamometers. In this paper, we construct a simulation model of an electric vehicle system using Matlab Simulink, and confirm the response characteristics based on the vehicle test driving profiles. In addition, we show that it is possible to derive the correlation between the SoC, voltage, and current of the battery according to the driving time of the electric vehicle in conjunction with the BMS model.

• Journal of Power Electronics
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• v.18 no.4
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• pp.1211-1222
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• 2018

This study presents a power distribution control scheme for a three-phase interleaved parallel DC/DC converter in a battery energy storage system. To extend battery life and increase the power equalization rate, a control method based on the nth order of the state of charge (SoC) is proposed for the charging and discharging processes. In the discharging process, the battery sets with high SoC deliver more power, whereas those with low SoC deliver less power. Therefore, the SoC between each battery set gradually decreases. However, in the two-stage charging process, the battery sets with high SoC absorb less power, and thus, a power correction algorithm is proposed to prevent the power of each particular battery set from exceeding its rated power. In the simulation performed with MATLAB/Simulink, results show that the proposed scheme can rapidly and effectively control the power distribution of the battery sets in the charging and discharging processes.

• Transactions of the Korean hydrogen and new energy society
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• v.20 no.1
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• pp.38-44
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• 2009

Recently, the research focused on fuel cell hybrid vehicles (FCHVs) is becoming an attractive solution due to environmental pollution generated by fossil fuel vehicles. The proper energy control strategy will result in extending the fuel cell lifetime, increasing of energy efficiency and an improvement of vehicle performance. Battery state of charge (SoC) is an important quantity and the estimation of the SoC is also the basis of the energy control strategy for hybrid electric vehicles. Estimating the battery's SoC is complicated by the fact that the SoC depends on many factors such as temperature, battery capacitance and internal resistance. In this paper, battery charging time estimated by SoC is studied by using the speed response and current response. Hybrid system is consist of a fuel cell unit and a battery in series connection. For experiment, speed response of vehicle and current response of battery were determined under different state of charge. As the results, the optimal battery charging time can be estimated. Current response time was faster than RPM response time at low speed and vice versa at high speed.

• Transactions of the Korean hydrogen and new energy society
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• v.15 no.1
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• pp.1-11
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• 2004

Hybrid power systems with fuel cells and batteries have the potential to improve the operation efficiency and dynamic response. A proper load management strategy is important to better system efficiency and endurance in hybrid systems. In this paper, a fuzzy logic algorithm has been used to determine the fuel cell output power depending on the external required power and the battery state of charge(SoC). If the required power of the hybrid system is small and the SoC is small, then the greater part of the fuel cell power is used to charge the battery pack. If the required power is relatively big and the SoC is big, then fuel cell and battery are concurrently used to supply the required power. These IF-THEN operation rules are implemented by fuzzy logic for the energy management system of hybrid system. The strategy is evaluated by simulation. The results show that fuzzy logic can be effectively used to optimize the operational efficiency of hybrid system and to maintain the battery SoC properly.

• 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 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 Power Electronics
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• v.13 no.4
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• pp.569-583
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• 2013

In this study, the simultaneous use of a multi-level converter (MLC) as a DC-motor drive and as an active battery cell balancer is investigated. MLCs allow each battery cell in a battery pack to be independently switched on and off, thereby enabling the potential non-uniform use of battery cells. By exploiting this property and the brake regeneration phases in the drive cycle, MLCs can balance both the state of charge (SoC) and temperature differences between cells, which are two known causes of battery wear, even without reciprocating the coolant flow inside the pack. The optimal control policy (OP) that considers both battery pack temperature and SoC dynamics is studied in detail based on the assumption that information on the state of each cell, the schedule of reciprocating air flow and the future driving profile are perfectly known. Results show that OP provides significant reductions in temperature and in SoC deviations compared with the uniform use of all cells even with uni-directional coolant flow. Thus, reciprocating coolant flow is a redundant function for a MLC-based cell balancer. A specific contribution of this paper is the derivation of a state-space electro-thermal model of a battery submodule for both uni-directional and reciprocating coolant flows under the switching action of MLC, resulting in OP being derived by the solution of a convex optimization problem.

• Journal of Power Electronics
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• v.13 no.4
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• pp.516-527
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• 2013

This paper presents a new overall system for state-of-available-power (SoAP) prediction for a lithium-ion battery pack. The essential part of this method is based on an adaptive network architecture which utilizes both fuzzy model (FIS) and artificial neural network (ANN) into the framework of adaptive neuro-fuzzy inference system (ANFIS). While battery aging proceeds, the system is capable of delivering accurate power prediction not only for room temperature, but also at lower temperatures at which power prediction is most challenging. Due to design property of ANN, the network parameters are adapted on-line to the current battery states (state-of-charge (SoC), state-of-health (SoH), temperature). SoC is required as an input parameter to SoAP module and high accuracy is crucial for a reliable on-line adaptation. Therefore, a reasonable way to determine the battery state variables is proposed applying a combination of several partly different algorithms. Among other SoC boundary estimation methods, robust extended Kalman filter (REKF) for recalibration of amp hour counters was implemented. ANFIS then achieves the SoAP estimation by means of time forward voltage prognosis (TFVP) before a power pulse occurs. The trade-off between computational cost of batch-learning and accuracy during on-line adaptation was optimized resulting in a real-time system with TFVP absolute error less than 1%. The verification was performed on a software-in-the-loop test bench setup using a 53 Ah lithium-ion cell.

• Proceedings of the KIEE Conference
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• 1996.07c
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• pp.1412-1413
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• 1996

Li ion battery have many advantages such as high energy density, high voltage and low self discharge, so it will replace conventional Ni/Cd battery. But, charge-discharge characterization of Li battery is controlled by weight ratio of electrodes (Cathode/Anode). So, we performed a study on relation between charge/discharge characterization and weight ratio (cathode/anode).