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State of Charge Estimation Method of Lead-Acid Battery Based on Multi-parameter Fusion

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Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019 (AISI 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1058))

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Abstract

Under the background of energy crisis, new energy power generation technology develops continuously along with the gradual increase of power demand. Energy storage technology plays a very important role in the new energy power generation and grid operation safety. Currently, as the most widely used and developed equipment in the field of energy storage, battery has a significant impact on the safety and stability of people’s life and the steady development of economy. Therefore, it is helpful to predict the health condition of the battery and replace the used battery in time to avoid power accidents and improve the reliability of the power grid. In this paper, an improved SOC estimation method is proposed based on the combination of open-circuit voltage method and ampere hour integral method. SOC initialization algorithm combining multiple parameters and introducing weight w is studied. In the SOC estimation process, the battery capacity is calibrated according to real-time temperature, which can improve the calculation accuracy and meet the operating conditions.

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Acknowledgments

This work is supported by the Science and Technology Program of Shenyang under Grant 18-013-0-18 and the National Nature Science Foundation of Liaoning Province under Grant 20180550922.

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Authors and Affiliations

  1. College of International Education, Shenyang Institute of Technology, Shenyang, 110136, China

    Yuan Yu

Authors
  1. Yuan Yu
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Corresponding author

Correspondence to Yuan Yu .

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Editors and Affiliations

  1. Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  2. The British University in Dubai, Dubai, United Arab Emirates

    Khaled Shaalan

  3. Ain Shams University, Cairo, Egypt

    Mohamed Fahmy Tolba

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Yu, Y. (2020). State of Charge Estimation Method of Lead-Acid Battery Based on Multi-parameter Fusion. In: Hassanien, A., Shaalan, K., Tolba, M. (eds) Proceedings of the International Conference on Advanced Intelligent Systems and Informatics 2019. AISI 2019. Advances in Intelligent Systems and Computing, vol 1058. Springer, Cham. https://doi.org/10.1007/978-3-030-31129-2_103

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