• Title, Summary, Keyword: Battery State Estimation

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State of Charge Estimation of Li-Ion Battery Based on CIM and OCV Using Extended Kalman Filter (전류적산법과 OCV 방법을 결합한 Li-Ion 배터리의 충전상태 추정)

  • Park, Joung-Ho;Cha, Wang-Cheol;Cho, Uk-Rae;Kim, Jae-Chul
    • 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.

Sliding Mode Observer (SMO) using Aging Compensation based State-of-Charge(SOC) Estimation for Li-Ion Battery Pack

  • Kim, Jonghoon;Nikitenkov, Dmitry;Denisova, Valeria
    • Proceedings of the KIPE Conference
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    • pp.200-201
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    • 2013
  • This paper investigates a new approach for Li-Ion battery state-of-charge (SOC) estimation using sliding mode observer (SMO) technique including parameters aging compensation via recursive least squares (RLS). The main advantages of this approach would be low computational load, easiness of implementation along with the robustness of the method for internal battery model parameters estimation. The proposed algorithm was first tested on a set of acquired battery data using implementation in Simulink and later developed as C-code module for firmware application.

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Adaptive State-of-Charge Estimation Method for an Aeronautical Lithium-ion Battery Pack Based on a Reduced Particle-unscented Kalman Filter

  • Wang, Shun-Li;Yu, Chun-Mei;Fernandez, Carlos;Chen, Ming-Jie;Li, Gui-Lin;Liu, Xiao-Han
    • Journal of Power Electronics
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    • v.18 no.4
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    • pp.1127-1139
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    • 2018
  • A reduced particle-unscented Kalman filter estimation method, along with a splice-equivalent circuit model, is proposed for the state-of-charge estimation of an aeronautical lithium-ion battery pack. The linearization treatment is not required in this method and only a few sigma data points are used, which reduce the computational requirement of state-of-charge estimation. This method also improves the estimation covariance properties by introducing the equilibrium parameter state of balance for the aeronautical lithium-ion battery pack. In addition, the estimation performance is validated by the experimental results. The proposed state-of-charge estimation method exhibits a root-mean-square error value of 1.42% and a mean error value of 4.96%. This method is insensitive to the parameter variation of the splice-equivalent circuit model, and thus, it plays an important role in the popularization and application of the aeronautical lithium-ion battery pack.

Hysteresis Modeling of the Sealed Flooded Lead Acid Battery for SOC Estimation (SOC 추정을 위한 밀폐형 Flooded 연축전지의 히스테리시스 모델링)

  • Khan, Abdul Basit;Choi, Woojin
    • Proceedings of the KIPE Conference
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    • pp.309-310
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    • 2016
  • Sealed flooded lead acid batteries are becoming popular in the industry because of their low cost as compared to their counterparts. State of Charge (SOC) estimation has always been an important factor in battery management systems. For the accurate SOC estimation, open circuit voltage (OCV) hysteresis should be modelled accurately. The hysteresis phenomenon of the sealed flooded lead acid battery is discussed in detail and its ultimate modeling is proposed based on the conventional parallelogram method. The SOC estimation is performed by using Unscented Kalman Filter (UKF) while the parameters of the battery are estimated using Auto Regressive with external input (ARX) method. The validity of the proposed method is verified by the experimental results. The SOC estimation error by the proposed method is less than 3 % all wing the 125hr test.

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An Efficient Battery Charging Algorithm based on State-of-Charge Estimation using 3-Phase AC-DC Boost Converter (3상 AC-DC 승압형 컨버터를 이용한 SOC 추정 기반의 효율적 배터리 충전 알고리즘)

  • Lee, Jung-Hyo;Won, Chung-Yuen
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.29 no.9
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    • pp.96-102
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    • 2015
  • This paper presents battery charging method using 3-phase AC-DC boost converter. General battery charging method is that charging the battery voltage to the reference voltage according to the constant current(CC) control, when it reaches the reference voltage, charging the battery fully according to the constant voltage(CV) control. However, battery chaging time is increased because of the battery impedance, constant current charging section which shoud take the large amount of charge is narrow, and constant voltage charging section which can generate insufficient charge is widen. To improve this problem, we proposes the method to reduce the charging time according to the SOC(State of Charge) estimation using battery impedance.

Novel Estimation Technique for the State-of-Charge of the Lead-Acid Battery by using EKF Considering Diffusion and Hysteresis Phenomenon (확산 및 히스테리시스 현상을 고려한 확장칼만필터를 이용한 새로운 납축전지의 충전상태 추정방법)

  • Duong, Van-Huan;Tran, Ngoc-Tham;Park, Yong-Jin;Choi, Woojin
    • The Transactions of the Korean Institute of Power Electronics
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    • v.19 no.2
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    • pp.139-148
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    • 2014
  • State-of-charge (SOC) is one of the significant indicators to estimate the driving range of the electric vehicle and to control the alternator of the conventional engine vehicles as well. Therefore its precise estimation is crucial not only for utilizing the energy effectively but also preventing critical situations happening to the power train and lengthening the lifetime of the battery. However, lead-acid battery is time-variant, highly nonlinear, and the hysteresis phenomenon causes large errors in estimation SOC of the battery especially under the frequent discharge/charge. This paper proposes a novel estimation technique for the SOC of the Lead-Acid battery by using a well-known Extended Kalman Filter (EKF) and an electrical equivalent circuit model of the Lead-Acid battery considering diffusion and hysteresis characteristics. The diffusion is considered by the reconstruction of the open circuit voltage decay depending on the rest time and the hysteresis effect is modeled by calculating the normalized integration of the charge throughput during the partial cycle. The validity of the proposed algorithm is verified through the experiments.

Battery State-of-Charge Estimation Algorithm Using Dynamic Terminal Voltage Measurement

  • Lee, Su-Hyeok;Lee, Seong-Won
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.126-131
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    • 2015
  • When a battery is discharging, the battery's current and terminal voltage must both be measured to estimate its state of charge (SOC). If the SOC can be estimated by using only the current or voltage, hardware costs will decrease. This paper proposes an SOC estimation algorithm that needs to measure only the terminal voltage while a battery is discharging. The battery's SOC can be deduced from its open circuit voltage (OCV) through the relationship between SOC and OCV. But when the battery is discharging, it is not possible to measure the OCV due to the voltage drop in the battery's internal resistance (IRdrop). The proposed algorithm calculates OCV by estimating IRdrop using a dynamic terminal voltage measurement. This paper confirms the results of applying the algorithm in a hardware environment via algorithm binarization. To evaluate the algorithm, a Simulink battery model based on actual values was used.

The SOC, Capacity-fade, Resistance-fade Estimation Technique using Sliding Mode Observer for Hybrid Electric Vehicle Lithium Battery (하이브리드 자동차용 리튬배터리의 충전량, 용량감퇴, 저항감퇴 예측을 위한 슬라이딩 모드 관측기 설계)

  • Kim, Il-Song;Lhee, Chin-Gook
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.5
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    • pp.839-844
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    • 2008
  • A novel state of health estimation method for hybrid electric vehicle lithium battery using sliding mode observer has been presented. A simple R-C circuit method has been used for the lithium battery modeling for the reduced calculation time and system resources due to the simple matrix operations. The modeling errors of simple model are compensated by the sliding mode observer. The design methodology for state of health estimation using dual sliding mode observer has been presented in step by step. The structure of the proposed system is simple and easy to implement, but it shows robust control property against modeling errors and temperature variations. The convergence of proposed observer system has been proved by the Lyapunov inequality equation and the performance of system has been verified by the sequence of urban dynamometer driving schedule test. The test results show the proposed observer system has superior tracking performance with reduced calculation time under the real driving environments.