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Cranking Capability Estimation Algorithm Based on Modeling and Online Update of Model Parameters for Li-Ion SLI Batteries

Author

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  • Tae-Won Noh

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do 16419, Korea)

  • Jung-Hoon Ahn

    (Energy Convergence Research Center, Korea Electronics Technology Institute (KETI), 226, Cheomdangwagi-ro, Buk-gu, Gwangju 61011, Korea)

  • Byoung Kuk Lee

    (Department of Electrical and Computer Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Suwon-si, Gyeonggi-do 16419, Korea)

Abstract

The terminal voltage of a starting–lighting–ignition (SLI) battery can decrease to a value lower than the allowable voltage range because of the high discharge current required to crank the engine of a vehicle. To avoid the safety problems generated by this voltage drop, this paper proposes a cranking capability estimation algorithm. The proposed algorithm includes an equivalent circuit model for describing the instantaneous voltage response to the cranking current profile. This algorithm predicts the minimum value of the terminal voltage for the cranking transient period by analyzing the polarization voltage and dynamic characteristic of the equivalent circuit model. The estimation accuracy is adjusted by an online update for the parameters of the equivalent circuit model, which varies with temperature, aging, and other factors. The proposed algorithm was validated by experiments with a 60Ah LiFePO4-type SLI battery.

Suggested Citation

  • Tae-Won Noh & Jung-Hoon Ahn & Byoung Kuk Lee, 2019. "Cranking Capability Estimation Algorithm Based on Modeling and Online Update of Model Parameters for Li-Ion SLI Batteries," Energies, MDPI, vol. 12(17), pages 1-14, September.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:17:p:3365-:d:262943
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    References listed on IDEAS

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    1. Berecibar, Maitane & Garmendia, Maitane & Gandiaga, Iñigo & Crego, Jon & Villarreal, Igor, 2016. "State of health estimation algorithm of LiFePO4 battery packs based on differential voltage curves for battery management system application," Energy, Elsevier, vol. 103(C), pages 784-796.
    2. Lei Zhang & Zhenpo Wang & Fengchun Sun & David G. Dorrell, 2014. "Online Parameter Identification of Ultracapacitor Models Using the Extended Kalman Filter," Energies, MDPI, vol. 7(5), pages 1-14, May.
    3. Farmann, Alexander & Sauer, Dirk Uwe, 2018. "Comparative study of reduced order equivalent circuit models for on-board state-of-available-power prediction of lithium-ion batteries in electric vehicles," Applied Energy, Elsevier, vol. 225(C), pages 1102-1122.
    4. Wang, Kangkang & Gao, Fei & Zhu, Yanli & Liu, Hao & Qi, Chuang & Yang, Kai & Jiao, Qingjie, 2018. "Internal resistance and heat generation of soft package Li4Ti5O12 battery during charge and discharge," Energy, Elsevier, vol. 149(C), pages 364-374.
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    Cited by:

    1. Nickolay I. Shchurov & Sergey I. Dedov & Boris V. Malozyomov & Alexander A. Shtang & Nikita V. Martyushev & Roman V. Klyuev & Sergey N. Andriashin, 2021. "Degradation of Lithium-Ion Batteries in an Electric Transport Complex," Energies, MDPI, vol. 14(23), pages 1-33, December.
    2. Tae-Won Noh & Junghoon Ahn & Byoung Kuk Lee, 2022. "Online Cell Screening Algorithm for Maximum Peak Current Estimation of a Lithium-Ion Battery Pack for Electric Vehicles," Energies, MDPI, vol. 15(4), pages 1-14, February.
    3. Andre T. Puati Zau & Mpho J. Lencwe & S. P. Daniel Chowdhury & Thomas O. Olwal, 2022. "A Battery Management Strategy in a Lead-Acid and Lithium-Ion Hybrid Battery Energy Storage System for Conventional Transport Vehicles," Energies, MDPI, vol. 15(7), pages 1-29, April.

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