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Comprehensive Model for Real Battery Simulation Responsive to Variable Load

Author

Listed:
  • Gustavo Piske Fenner

    (Electromechanical and Power Systems Department, Federal University of Santa Maria–UFSM, Santa Maria 97105-900, Brazil)

  • Leonardo Weber Stringini

    (Electromechanical and Power Systems Department, Federal University of Santa Maria–UFSM, Santa Maria 97105-900, Brazil)

  • Camilo Alberto Sepulveda Rangel

    (Electromechanical and Power Systems Department, Federal University of Santa Maria–UFSM, Santa Maria 97105-900, Brazil)

  • Luciane Neves Canha

    (Electromechanical and Power Systems Department, Federal University of Santa Maria–UFSM, Santa Maria 97105-900, Brazil)

Abstract

This paper proposes a battery voltage model that is suitable for variable operation. The model combines the features of the Kinetic Battery Model (KiBaM) and voltage model (VM), and it improves the accuracy and quality of the solution, addressing four characteristics of operation: charging, discharging, rest after charge, and rest after discharge. This model will be known as 4-KiVM and shows low impact on computational burden. The proposed model can keep track of the voltage even when the load is inverted or turned off. To calibrate and validate the model, a NASA-provided dataset was used composed of a battery with variable charges and discharges, simulating real applications. A metaheuristic method based on tabu search is used to extract constants from this dataset and validate this hybrid model. In addition, a comparison of performance of the 4-KiVM against KiBaM, VM, and the electric circuit model (ECM) was made, showing its advantages. The results of the simulations showed a good prediction of the battery voltage response and SOC prediction in random (variable) use.

Suggested Citation

  • Gustavo Piske Fenner & Leonardo Weber Stringini & Camilo Alberto Sepulveda Rangel & Luciane Neves Canha, 2021. "Comprehensive Model for Real Battery Simulation Responsive to Variable Load," Energies, MDPI, vol. 14(11), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3209-:d:565895
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    References listed on IDEAS

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    1. Wang, Yujie & Tian, Jiaqiang & Sun, Zhendong & Wang, Li & Xu, Ruilong & Li, Mince & Chen, Zonghai, 2020. "A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    2. Wei, Zhongbao & Meng, Shujuan & Xiong, Binyu & Ji, Dongxu & Tseng, King Jet, 2016. "Enhanced online model identification and state of charge estimation for lithium-ion battery with a FBCRLS based observer," Applied Energy, Elsevier, vol. 181(C), pages 332-341.
    3. Diouf, Boucar & Pode, Ramchandra, 2015. "Potential of lithium-ion batteries in renewable energy," Renewable Energy, Elsevier, vol. 76(C), pages 375-380.
    4. Fred Glover, 1990. "Tabu Search: A Tutorial," Interfaces, INFORMS, vol. 20(4), pages 74-94, August.
    5. He, Hongwen & Zhang, Xiaowei & Xiong, Rui & Xu, Yongli & Guo, Hongqiang, 2012. "Online model-based estimation of state-of-charge and open-circuit voltage of lithium-ion batteries in electric vehicles," Energy, Elsevier, vol. 39(1), pages 310-318.
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    Cited by:

    1. Gianfranco Chicco & Andrea Mazza & Salvatore Musumeci & Enrico Pons & Angela Russo, 2022. "Editorial for the Special Issue “Verifying the Targets—Selected Papers from the 55th International Universities Power Engineering Conference (UPEC 2020)”," Energies, MDPI, vol. 15(15), pages 1-8, August.

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