• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.7-14
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• 2020

A Battery Monitoring System capable of State-of-Charge(SOC) estimation using the Extended Kalman Filter(EKF) is described in this paper. In order to accurately estimate the SOC of the battery, the battery cells were modeled as the Thevenin equivalent circuit model. The Thevenin model's parameters were measured in experiments. For the Battery Monitoring System, we designed a battery monitoring device that can calculate the SOC estimation using the EKF and a monitoring server that controls multiple battery monitoring devices. We also develop a web-based dashboard for controlling and monitoring batteries. Especially the computation of the monitoring server could be reduced by calculating the battery SOC estimation at each Battery Monitoring Device.

• 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.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.11
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• pp.77-83
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• 2014

The Estimation of State of Charge(SOC) for batteries is an important aspect of a Battery Management System(BMS). A method for estimating the SOC is proposed in order to overcome the individual disadvantages of the current integral and Open Circuit Voltage(OCV) estimation methods by combining them using Extended Kalman filter(EKF). The non-linear characteristics of the Li-Ion RC battery model used in this study is also solved through EKF. The proposed method is simulated in a Matlab environment with a Li-Ion Kokam battery (3.7V, 1,500mAh). Results showed that there is an improvement in the estimation error when using the proposed model compared to the conventional current integral method.

• Proceedings of the KIPE Conference
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• 2016.11a
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• pp.59-60
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• 2016

Flooded lead acid batteries are still very popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation is of great importance for a flooded lead acid battery to ensure its safe working and to prevent it from over-charging or over-discharging. Different types of Kalman Filters are widely used for SOC estimation of batteries. The values of process and measurement noise covariance of a filter are usually calculated by trial and error method and taken as constant throughout the estimation process. While in practical cases, these values can vary as well depending upon the dynamics of the system. Therefore an Adaptive Unscented Kalman Filter (AUKF) is introduced in which the values of the process and measurement noise covariance are updated in each iteration based on the residual system error. A comparison of traditional and Adaptive Unscented Kalman Filter is presented in the paper. The results show that SOC estimation error by the proposed method is further reduced by 3 % as compared to traditional Unscented Kalman Filter.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.05a
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• pp.321-324
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• 2008

This paper presents the battery management system(BMS) for the optimum conditions of the lead-Acid battery in UPS. The proposed system controls the over and under currents of battery for protecting and it was applied algorithm for optimum conditions to estimate the State Of Charge(SOC) in charge or discharge mode. It approved the performance and the algorithm for the estimation of SOC, through the experiments which using the charge and discharge tester and the field tests.

• Proceedings of the KIPE Conference
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• 2011.11a
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• pp.32-33
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• 2011

Recently, researches on SOC(State Of Charge) of batteries are being increased. Techniques of measuring the battery SOC is essential to researches on increasing cycle life of batteries and to electric vehicle battery charging systems. The surface charge phenomenon of lead storage batteries and the needs of SOC measuring techniques are considered. Features of SOC measuring techniques that have been recently developed are also considered.

• Journal of Power Electronics
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• v.17 no.6
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• pp.1625-1636
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• 2017

A power electronic transformer (PET) based on the cascaded H-bridge (CHB) and the isolated bidirectional DC/DC converter (IBDC) is capable of accommodating a large scale battery energy storage system (BESS) in the medium-voltage grid, and is referred to as a power electronic transformer based battery energy storage system (PET-BESS). This paper investigates the PET-BESS and proposes a coordinative control strategy for it. In the proposed method, the CHB controls the power flow and the battery state-of-charge (SOC) balancing, while the IBDC maintains the dc-link voltages with feedforward implementation of the power reference and the switch status of the CHB. State-feedback and linear quadratic Riccati (LQR) methods have been adopted in the CHB to control the grid current, active power and reactive power. A hybrid PWM modulating method is utilized to achieve SOC balancing, where battery SOC sorting is involved. The feedforward path of the power reference and the CHB switch status substantially reduces the dc-link voltage fluctuations under dynamic power variations. The effectiveness of the proposed control has been verified both by simulation and experimental results. The performance of the PET-BESS under bidirectional power flow has been improved, and the battery SOC values have been adjusted to converge.

• Journal of Power Electronics
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• v.9 no.3
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• pp.472-480
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• 2009

In this paper, a charge equalization converter with parallel-connected primary windings of transformers is proposed. The proposed work effectively balances the voltage among Lithium-Ion battery cells despite each battery cell has low voltage gap compared with its state of charge (SOC). The principle of the proposed work is that the equalizing energy from all battery strings moves to the lowest voltage battery through the isolated dc/dc converter controlled by the corresponding solid state relay switch. For this research a prototype of four Lithium-Ion battery cells is optimally designed and implemented, and experimental results show that the proposed method has excellent cell balancing performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.4
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• pp.529-536
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• 2015

With the growing interest of microgrid all over the world, many studies on microgrid operation are being carried out. The battery energy storage system(BESS) is a key equipment for effective operation of the microgrid. In this paper, we analyze the characteristics of the charge and discharge output voltage of the battery and the characteristics of the life-span variation and the investment cost when the state-of-charge (SOC) changes. The formulas to represent the quality of the charge and discharge output voltage of the battery and the economics due to the life-span variation and the investment cost according to DOD(Depth of Discharge) are derived. The methodology of determining the proper operation ranges of the battery SOC with varying the weighting of the quality of its charge and discharge output voltage of the battery and the economics due to its life-span variation and the investment cost is presented using these formulas.

• Proceedings of the KIPE Conference
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• 2019.11a
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• pp.174-175
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• 2019

Battery cells are connected in parallel to enlarge the system capacity. However, cell inconsistency may reduce the overall system capacity and cause the over-charging or over-discharging issue. This paper proposes a SOC-based sequencing equalizer for parallel-connected battery configuration that uses the ANFIS (adaptive neuro-fuzzy inference system) algorithm to make the switching decision. Depend on the load current and the SOC (state-of-charge) rate of cells, the switching decision is made to equalize the SOC of the battery cells. The simulation results show that the system capacity is maximized and the controller is adaptive for a large number of parallel-connected in dynamic load profile.