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Electrochemical-Thermal Modelling and Optimisation of Lithium-Ion Battery Design Parameters Using Analysis of Variance

Author

Listed:
  • Elham Hosseinzadeh

    (Warwick Manufacturing Group, International Digital Laboratory, University of Warwick, Coventry CV4 7AL, UK)

  • James Marco

    (Warwick Manufacturing Group, International Digital Laboratory, University of Warwick, Coventry CV4 7AL, UK)

  • Paul Jennings

    (Warwick Manufacturing Group, International Digital Laboratory, University of Warwick, Coventry CV4 7AL, UK)

Abstract

A 1D electrochemical-thermal model of an electrode pair of a lithium ion battery is developed in Comsol Multiphysics. The mathematical model is validated against the literature data for a 10 Ah lithium phosphate (LFP) pouch cell operating under 1 C to 5 C electrical load at 25 °C ambient temperature. The validated model is used to conduct statistical analysis of the most influential parameters that dictate cell performance; i.e., particle radius ( r p ); electrode thickness ( L p o s ); volume fraction of the active material ( ε s , p o s ) and C-rate; and their interaction on the two main responses; namely; specific energy and specific power. To achieve an optimised window for energy and power within the defined range of design variables; the range of variation of the variables is determined based on literature data and includes: r p : 30–100 nm; L p o s : 20–100 μm; ε s , p o s : 0.3–0.7; C-rate: 1–5. By investigating the main effect and the interaction effect of the design variables on energy and power; it is observed that the optimum energy can be achieved when ( r p < 40 nm); (75 μm < L pos < 100 μm); (0.4 < ε s,pos < 0.6) and while the C-rate is below 4C. Conversely; the optimum power is achieved for a thin electrode ( L p o s < 30 μm); with high porosity and high C-rate (5 C).

Suggested Citation

  • Elham Hosseinzadeh & James Marco & Paul Jennings, 2017. "Electrochemical-Thermal Modelling and Optimisation of Lithium-Ion Battery Design Parameters Using Analysis of Variance," Energies, MDPI, vol. 10(9), pages 1-22, August.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:9:p:1278-:d:110060
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    References listed on IDEAS

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    1. Su, Laisuo & Zhang, Jianbo & Wang, Caijuan & Zhang, Yakun & Li, Zhe & Song, Yang & Jin, Ting & Ma, Zhao, 2016. "Identifying main factors of capacity fading in lithium ion cells using orthogonal design of experiments," Applied Energy, Elsevier, vol. 163(C), pages 201-210.
    2. Cheng, Shan-Jen & Miao, Jr-Ming & Wu, Sheng-Ju, 2012. "Investigating the effects of operational factors on PEMFC performance based on CFD simulations using a three-level full-factorial design," Renewable Energy, Elsevier, vol. 39(1), pages 250-260.
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    Cited by:

    1. Couto, Luis. D. & Charkhgard, Mohammad & Karaman, Berke & Job, Nathalie & Kinnaert, Michel, 2023. "Lithium-ion battery design optimization based on a dimensionless reduced-order electrochemical model," Energy, Elsevier, vol. 263(PE).
    2. Yoon Koo Lee, 2019. "The Effect of Active Material, Conductive Additives, and Binder in a Cathode Composite Electrode on Battery Performance," Energies, MDPI, vol. 12(4), pages 1-19, February.
    3. Astaneh, Majid & Andric, Jelena & Löfdahl, Lennart & Stopp, Peter, 2022. "Multiphysics simulation optimization framework for lithium-ion battery pack design for electric vehicle applications," Energy, Elsevier, vol. 239(PB).
    4. Yong Li & Jue Yang & Wei Long Liu & Cheng Lin Liao, 2020. "Multi-Level Model Reduction and Data-Driven Identification of the Lithium-Ion Battery," Energies, MDPI, vol. 13(15), pages 1-23, July.
    5. Román-Ramírez, L.A. & Marco, J., 2022. "Design of experiments applied to lithium-ion batteries: A literature review," Applied Energy, Elsevier, vol. 320(C).
    6. 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.
    7. Lin Du & Yubo Wang & Wujing Wang & Xiangxiang Chen, 2018. "Studies on a Thermal Fault Simulation Device and the Pyrolysis Process of Insulating Oil," Energies, MDPI, vol. 11(12), pages 1-16, December.
    8. Cheng Siong Chin & Zuchang Gao & Joel Hay King Chiew & Caizhi Zhang, 2018. "Nonlinear Temperature-Dependent State Model of Cylindrical LiFePO 4 Battery for Open-Circuit Voltage, Terminal Voltage and State-of-Charge Estimation with Extended Kalman Filter," Energies, MDPI, vol. 11(9), pages 1-28, September.

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