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Conference on Automation

AUTOMATION 2019: Automation 2019 pp 218–231Cite as

Battery Voltage Estimation Using NARX Recurrent Neural Network Model

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 920))

Abstract

This work presents a prediction of battery terminal voltage in subsequent charging/discharging cycles. To estimate chosen signals the NARX (AutoRegressive with eXogenous input) model based on Recurrent Neural Network has been employed. A training and testing data were gathered at the laboratory test stand with the Lithium Iron Phosphate (LiFePO4) battery in different working conditions. Test stand research was conducted for 40 charging/discharging cycles. Furthermore, the paper presents the results of the identification of double RC model parameters for a specified state of charge level. As a result, the analysis of the proposed methodology has been discussed.

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Notes

  1. 1.

    The NRSME index vary between \( - \infty \) (no fit) to 1 (perfect fit).

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Author information

Authors and Affiliations

  1. Institute of Vehicles, Warsaw University of Technology, Narbutta 84 Street, Warsaw, Poland

    Adrian Chmielewski & Krzysztof Bogdziński

  2. Institute of Automatic Control and Robotics, Warsaw University of Technology, Sw. A. Boboli 8, Warsaw, Poland

    Jakub Możaryn

  3. Institute of Construction Machinery Engineering, Warsaw University of Technology, Narbutta 84 Street, Warsaw, Poland

    Piotr Piórkowski

Authors
  1. Adrian Chmielewski
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  2. Jakub Możaryn
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  3. Piotr Piórkowski
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  4. Krzysztof Bogdziński
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Corresponding author

Correspondence to Adrian Chmielewski .

Editor information

Editors and Affiliations

  1. Industrial Research Institute for Automation and Measurements PIAP Al, Warsaw, Poland

    Roman Szewczyk

  2. Industrial Research Institute for Automation and Measurements PIAP Al, Warsaw, Poland

    Cezary Zieliński

  3. Industrial Research Institute for Automation and Measurements PIAP Al, Warsaw, Poland

    Małgorzata Kaliczyńska

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Chmielewski, A., Możaryn, J., Piórkowski, P., Bogdziński, K. (2020). Battery Voltage Estimation Using NARX Recurrent Neural Network Model. In: Szewczyk, R., Zieliński, C., Kaliczyńska, M. (eds) Automation 2019. AUTOMATION 2019. Advances in Intelligent Systems and Computing, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-030-13273-6_22

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