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An Acausal Li-Ion Battery Pack Model for Automotive Applications

Author

Listed:
  • Kotub Uddin

    (WMG, International Digital Laboratory, the University of Warwick, Coventry CV4 7AL, UK)

  • Alessandro Picarelli

    (Claytex Services Ltd., Edmund House, Rugby Road, Leamington Spa CV32 6EL, UK)

  • Christopher Lyness

    (Hybrids & Electrification, Jaguar & Land Rover, Banbury Road, Warwick CV35 0XJ, UK)

  • Nigel Taylor

    (Hybrids & Electrification, Jaguar & Land Rover, Banbury Road, Warwick CV35 0XJ, UK)

  • James Marco

    (WMG, International Digital Laboratory, the University of Warwick, Coventry CV4 7AL, UK)

Abstract

In this work, a novel acausal and reconfigurable battery pack model is presented. The model structure adopted for the battery cell is based on an equivalent circuit representation. The circuit elements are modified to take account of both hysteresis and diffusion limitation. The latter is known to be a nonlinear function of large operating currents or long operating times. It is shown that the integration of a current dependent time constant within the cell model better emulates the solid diffusional dynamics of lithium intercalation into the active material under large electrical loads. The advantages of an acausal modeling approach, when scaling-up individual cell models into a complete battery system are also presented. Particular consideration is given to emulating the impact of cell to cell variations on pack performance. Using statistical analysis of battery tests, cell model parameter variations are characterized and quantified. The cell and scaled-up pack model are parameterized for a number of commercially available cell formats, energy capacities and chemistries. The new models are validated using transient, real-world, electrical data measured from an electric vehicle (EV) operating within an urban environment.

Suggested Citation

  • Kotub Uddin & Alessandro Picarelli & Christopher Lyness & Nigel Taylor & James Marco, 2014. "An Acausal Li-Ion Battery Pack Model for Automotive Applications," Energies, MDPI, vol. 7(9), pages 1-26, August.
    • Handle: RePEc:gam:jeners:v:7:y:2014:i:9:p:5675-5700:d:39716
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    References listed on IDEAS

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    1. Peng Bai & Martin Z. Bazant, 2014. "Charge transfer kinetics at the solid–solid interface in porous electrodes," Nature Communications, Nature, vol. 5(1), pages 1-7, May.
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    3. An, Tae-Ho & Choi, Soon-Mok & Kim, Il-Ho & Kim, Sun-Uk & Seo, Won-Seon & Kim, Jong-Young & Park, Chan, 2012. "Thermoelectric properties of a doped Mg2Sn system," Renewable Energy, Elsevier, vol. 42(C), pages 23-27.
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    Citations

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    Cited by:

    1. Susanne Rothgang & Matthias Rogge & Jan Becker & Dirk Uwe Sauer, 2015. "Battery Design for Successful Electrification in Public Transport," Energies, MDPI, vol. 8(7), pages 1-23, June.
    2. Thomas R. B. Grandjean & Andrew McGordon & Paul A. Jennings, 2017. "Structural Identifiability of Equivalent Circuit Models for Li-Ion Batteries," Energies, MDPI, vol. 10(1), pages 1-16, January.
    3. Gaizka Saldaña & José Ignacio San Martín & Inmaculada Zamora & Francisco Javier Asensio & Oier Oñederra, 2019. "Analysis of the Current Electric Battery Models for Electric Vehicle Simulation," Energies, MDPI, vol. 12(14), pages 1-27, July.
    4. Sang-Won Lee & Yoon-Geol Choi & Bongkoo Kang, 2019. "Active Charge Equalizer of Li-Ion Battery Cells Using Double Energy Carriers," Energies, MDPI, vol. 12(12), pages 1-13, June.
    5. Uddin, Kotub & Gough, Rebecca & Radcliffe, Jonathan & Marco, James & Jennings, Paul, 2017. "Techno-economic analysis of the viability of residential photovoltaic systems using lithium-ion batteries for energy storage in the United Kingdom," Applied Energy, Elsevier, vol. 206(C), pages 12-21.
    6. Lan-Rong Dung & Hsiang-Fu Yuan & Jieh-Hwang Yen & Chien-Hua She & Ming-Han Lee, 2016. "A Lithium-Ion Battery Simulator Based on a Diffusion and Switching Overpotential Hybrid Model for Dynamic Discharging Behavior and Runtime Predictions," Energies, MDPI, vol. 9(1), pages 1-21, January.
    7. Allafi, Walid & Uddin, Kotub & Zhang, Cheng & Mazuir Raja Ahsan Sha, Raja & Marco, James, 2017. "On-line scheme for parameter estimation of nonlinear lithium ion battery equivalent circuit models using the simplified refined instrumental variable method for a modified Wiener continuous-time model," Applied Energy, Elsevier, vol. 204(C), pages 497-508.
    8. Bi, Jun & Zhang, Ting & Yu, Haiyang & Kang, Yanqiong, 2016. "State-of-health estimation of lithium-ion battery packs in electric vehicles based on genetic resampling particle filter," Applied Energy, Elsevier, vol. 182(C), pages 558-568.
    9. Majid Astaneh & Jelena Andric & Lennart Löfdahl & Dario Maggiolo & Peter Stopp & Mazyar Moghaddam & Michel Chapuis & Henrik Ström, 2020. "Calibration Optimization Methodology for Lithium-Ion Battery Pack Model for Electric Vehicles in Mining Applications," Energies, MDPI, vol. 13(14), pages 1-27, July.
    10. Gough, Rebecca & Dickerson, Charles & Rowley, Paul & Walsh, Chris, 2017. "Vehicle-to-grid feasibility: A techno-economic analysis of EV-based energy storage," Applied Energy, Elsevier, vol. 192(C), pages 12-23.

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