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Increasing energy utilization of battery energy storage via active multivariable fusion-driven balancing

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Listed:
  • Li, Penghua
  • Liu, Jianfei
  • Deng, Zhongwei
  • Yang, Yalian
  • Lin, Xianke
  • Couture, Jonathan
  • Hu, Xiaosong

Abstract

Inconsistencies between the cells in a battery pack can greatly limit the pack's cycle life and performance. This is why an integrated equalization management system (EMS) is necessary to limit these inconsistencies. This paper presents a novel multivariable fusion equalization strategy utilizing a fuzzy logic controller (FLC). This strategy begins by firstly analyzing the voltage inconsistencies within the battery pack and by proposing different equalization objectives. Secondly, a simplified model is created, which consists of a battery model and an equalization circuit model, which is then used as a predictive model. Thirdly, a top-bottom method and a predictive control method are proposed to the EMS based on the battery voltage and its state of charge (SOC). Lastly, the FLC is used to fuse these two strategies depending on the ratio of the current over the capacity (RCC). A battery pack setup is built to acquire experimental data, and a series of tests are used to verify the proposed method. The proposed multivariable fusion equalization achieves a 14.9% increase in computational efficiency, and the battery performance increases by 4.9% over a traditional equalization strategy.

Suggested Citation

  • Li, Penghua & Liu, Jianfei & Deng, Zhongwei & Yang, Yalian & Lin, Xianke & Couture, Jonathan & Hu, Xiaosong, 2022. "Increasing energy utilization of battery energy storage via active multivariable fusion-driven balancing," Energy, Elsevier, vol. 243(C).
    • Handle: RePEc:eee:energy:v:243:y:2022:i:c:s0360544221030218
    DOI: 10.1016/j.energy.2021.122772
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    References listed on IDEAS

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