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Accurate Estimation on the State-of-Charge of Lithium-Ion Battery Packs

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Broadband Communications, Networks, and Systems (BROADNETS 2021)

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Abstract

Lithium-ion batteries have been extensively used worldwide for energy storage and supply in electric vehicles and other devices. An accurate estimation of their state-of-charge (SoC) is essential to ensure their safety and protect them from the explosion caused by overcharge. Large amounts of training data are required for SoC estimation resulting in a great computational burden. Model-based observation method can effectively estimate battery SoC with a limited amount of data. This study applied a combined model, including a one-state hysteresis model and a resistor-capacitor (RC) model, to diminish the parameter estimation errors caused by the hysteresis phenomenon, increasing the estimation accuracy. The Luenberger observer was designed based on the hysteresis RC battery model and evaluated under dynamic stress test (DST) and federal urban driving schedule (FUDS). Our simulation results have shown that the hysteresis RC model has better performance in terms of SoC estimation accuracy using Luenberger observer. Additionally, after the investigation of communication technologies, 5G cellular network offers feasibility for real-time vehicle interaction.

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Authors and Affiliations

  1. RMIT University, Melbourne, Australia

    Mengying Chen, Fengling Han & Long Shi

  2. Harbin Institute of Technology, Harbin, China

    Yong Feng & Chen Xue

  3. UNSW, Sydney, Australia

    Chaojie Li

Authors
  1. Mengying Chen
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  2. Fengling Han
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  3. Long Shi
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  4. Yong Feng
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  5. Chen Xue
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  6. Chaojie Li
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Corresponding author

Correspondence to Mengying Chen .

Editor information

Editors and Affiliations

  1. La Trobe University, Bundoora, VIC, Australia

    Wei Xiang

  2. RMIT University, Melbourne, VIC, Australia

    Fengling Han

  3. La Trobe University, Melbourne, VIC, Australia

    Tran Khoa Phan

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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Chen, M., Han, F., Shi, L., Feng, Y., Xue, C., Li, C. (2022). Accurate Estimation on the State-of-Charge of Lithium-Ion Battery Packs. In: Xiang, W., Han, F., Phan, T.K. (eds) Broadband Communications, Networks, and Systems. BROADNETS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 413. Springer, Cham. https://doi.org/10.1007/978-3-030-93479-8_17

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  • DOI: https://doi.org/10.1007/978-3-030-93479-8_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-93478-1

  • Online ISBN: 978-3-030-93479-8

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