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A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range

Author

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  • Fei Feng

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Rengui Lu

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

  • Chunbo Zhu

    (School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China)

Abstract

Ambient temperature is a significant factor that influences the characteristics of lithium-ion batteries, which can produce adverse effects on state of charge (SOC) estimation. In this paper, an integrated SOC algorithm that combines an advanced ampere-hour counting (Adv Ah) method and multistate open-circuit voltage (multi OCV) method, denoted as “Adv Ah + multi OCV”, is proposed. Ah counting is a simple and general method for estimating SOC. However, the available capacity and coulombic efficiency in this method are influenced by the operating states of batteries, such as temperature and current, thereby causing SOC estimation errors. To address this problem, an enhanced Ah counting method that can alter the available capacity and coulombic efficiency according to temperature is proposed during the SOC calculation. Moreover, the battery SOCs between different temperatures can be mutually converted in accordance with the capacity loss. To compensate for the accumulating errors in Ah counting caused by the low precision of current sensors and lack of accurate initial SOC, the OCV method is used for calibration and as a complement. Given the variation of available capacities at different temperatures, rated/non-rated OCV–SOCs are established to estimate the initial SOCs in accordance with the Ah counting SOCs. Two dynamic tests, namely, constant- and alternated - temperature tests, are employed to verify the combined method at different temperatures. The results indicate that our method can provide effective and accurate SOC estimation at different ambient temperatures.

Suggested Citation

  • Fei Feng & Rengui Lu & Chunbo Zhu, 2014. "A Combined State of Charge Estimation Method for Lithium-Ion Batteries Used in a Wide Ambient Temperature Range," Energies, MDPI, vol. 7(5), pages 1-29, May.
  • Handle: RePEc:gam:jeners:v:7:y:2014:i:5:p:3004-3032:d:35704
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    References listed on IDEAS

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    1. Ng, Kong Soon & Moo, Chin-Sien & Chen, Yi-Ping & Hsieh, Yao-Ching, 2009. "Enhanced coulomb counting method for estimating state-of-charge and state-of-health of lithium-ion batteries," Applied Energy, Elsevier, vol. 86(9), pages 1506-1511, September.
    2. Xing, Yinjiao & He, Wei & Pecht, Michael & Tsui, Kwok Leung, 2014. "State of charge estimation of lithium-ion batteries using the open-circuit voltage at various ambient temperatures," Applied Energy, Elsevier, vol. 113(C), pages 106-115.
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    Cited by:

    1. Ingvild B. Espedal & Asanthi Jinasena & Odne S. Burheim & Jacob J. Lamb, 2021. "Current Trends for State-of-Charge (SoC) Estimation in Lithium-Ion Battery Electric Vehicles," Energies, MDPI, vol. 14(11), pages 1-24, June.
    2. Yasser Diab & François Auger & Emmanuel Schaeffer & Moutassem Wahbeh, 2017. "Estimating Lithium-Ion Battery State of Charge and Parameters Using a Continuous-Discrete Extended Kalman Filter," Energies, MDPI, vol. 10(8), pages 1-19, July.
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    4. Duong, Van-Huan & Bastawrous, Hany Ayad & See, Khay Wai, 2017. "Accurate approach to the temperature effect on state of charge estimation in the LiFePO4 battery under dynamic load operation," Applied Energy, Elsevier, vol. 204(C), pages 560-571.
    5. Jiandong Duan & Peng Wang & Wentao Ma & Xinyu Qiu & Xuan Tian & Shuai Fang, 2020. "State of Charge Estimation of Lithium Battery Based on Improved Correntropy Extended Kalman Filter," Energies, MDPI, vol. 13(16), pages 1-18, August.
    6. Dai, Haifeng & Jiang, Bo & Hu, Xiaosong & Lin, Xianke & Wei, Xuezhe & Pecht, Michael, 2021. "Advanced battery management strategies for a sustainable energy future: Multilayer design concepts and research trends," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    7. Xiang Bao & Yuefeng Liu & Bo Liu & Haofeng Liu & Yue Wang, 2023. "Multi-State Online Estimation of Lithium-Ion Batteries Based on Multi-Task Learning," Energies, MDPI, vol. 16(7), pages 1-20, March.
    8. Feng, Fei & Yang, Rui & Meng, Jinhao & Xie, Yi & Zhang, Zhiguo & Chai, Yi & Mou, Lisha, 2022. "Electrochemical impedance characteristics at various conditions for commercial solid–liquid electrolyte lithium-ion batteries: Part. 2. Modeling and prediction," Energy, Elsevier, vol. 243(C).
    9. Hu, Lin & Hu, Xiaosong & Che, Yunhong & Feng, Fei & Lin, Xianke & Zhang, Zhiyong, 2020. "Reliable state of charge estimation of battery packs using fuzzy adaptive federated filtering," Applied Energy, Elsevier, vol. 262(C).
    10. Bachir Zine & Haithem Bia & Amel Benmouna & Mohamed Becherif & Mehroze Iqbal, 2022. "Experimentally Validated Coulomb Counting Method for Battery State-of-Charge Estimation under Variable Current Profiles," Energies, MDPI, vol. 15(21), pages 1-15, November.
    11. Xiaoyu Li & Kai Song & Guo Wei & Rengui Lu & Chunbo Zhu, 2015. "A Novel Grouping Method for Lithium Iron Phosphate Batteries Based on a Fractional Joint Kalman Filter and a New Modified K-Means Clustering Algorithm," Energies, MDPI, vol. 8(8), pages 1-26, July.
    12. Feng, Fei & Yang, Rui & Meng, Jinhao & Xie, Yi & Zhang, Zhiguo & Chai, Yi & Mou, Lisha, 2022. "Electrochemical impedance characteristics at various conditions for commercial solid–liquid electrolyte lithium-ion batteries: Part 1. experiment investigation and regression analysis," Energy, Elsevier, vol. 242(C).
    13. Xiaobin Hong & Nianzhi Li & Jinheng Feng & Qingzhao Kong & Guixiong Liu, 2015. "Multi-Electrode Resistivity Probe for Investigation of Local Temperature Inside Metal Shell Battery Cells via Resistivity: Experiments and Evaluation of Electrical Resistance Tomography," Energies, MDPI, vol. 8(2), pages 1-23, January.
    14. Xu, Xiaodong & Tang, Shengjin & Yu, Chuanqiang & Xie, Jian & Han, Xuebing & Ouyang, Minggao, 2021. "Remaining Useful Life Prediction of Lithium-ion Batteries Based on Wiener Process Under Time-Varying Temperature Condition," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    15. Fei Feng & Rengui Lu & Guo Wei & Chunbo Zhu, 2015. "Online Estimation of Model Parameters and State of Charge of LiFePO 4 Batteries Using a Novel Open-Circuit Voltage at Various Ambient Temperatures," Energies, MDPI, vol. 8(4), pages 1-27, April.
    16. Liqiang Zhang & Lixin Wang & Chao Lyu & Junfu Li & Jun Zheng, 2014. "Non-Destructive Analysis of Degradation Mechanisms in Cycle-Aged Graphite/LiCoO 2 Batteries," Energies, MDPI, vol. 7(10), pages 1-24, September.
    17. Bizhong Xia & Zhen Sun & Ruifeng Zhang & Zizhou Lao, 2017. "A Cubature Particle Filter Algorithm to Estimate the State of the Charge of Lithium-Ion Batteries Based on a Second-Order Equivalent Circuit Model," Energies, MDPI, vol. 10(4), pages 1-15, April.
    18. Zhichao He & Geng Yang & Languang Lu, 2016. "A Parameter Identification Method for Dynamics of Lithium Iron Phosphate Batteries Based on Step-Change Current Curves and Constant Current Curves," Energies, MDPI, vol. 9(6), pages 1-24, June.
    19. Shrivastava, Prashant & Soon, Tey Kok & Idris, Mohd Yamani Idna Bin & Mekhilef, Saad, 2019. "Overview of model-based online state-of-charge estimation using Kalman filter family for lithium-ion batteries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    20. Hong Zhang & Li Zhao & Yong Chen, 2015. "A Lossy Counting-Based State of Charge Estimation Method and Its Application to Electric Vehicles," Energies, MDPI, vol. 8(12), pages 1-18, December.

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