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Novel Fuzzy Control Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Considering State of Health

Author

Listed:
  • Xiao Hu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Shikun Liu

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Ke Song

    (School of Automotive Studies, Tongji University, Shanghai 201804, China
    National Fuel Cell Vehicle and Powertrain System Engineering Research Center, Tongji University, Shanghai 201804, China)

  • Yuan Gao

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

  • Tong Zhang

    (School of Automotive Studies, Tongji University, Shanghai 201804, China)

Abstract

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles.

Suggested Citation

  • Xiao Hu & Shikun Liu & Ke Song & Yuan Gao & Tong Zhang, 2021. "Novel Fuzzy Control Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Considering State of Health," Energies, MDPI, vol. 14(20), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6481-:d:653002
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    References listed on IDEAS

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    Cited by:

    1. Lianghui Huang & Quan Ouyang & Jian Chen & Zhiyang Liu & Xiaohua Wu, 2023. "A Scalable Segmented-Based PEM Fuel Cell Hybrid Power System Model and Its Simulation Applications," Energies, MDPI, vol. 16(17), pages 1-13, August.
    2. Mubashir Rasool & Muhammad Adil Khan & Runmin Zou, 2023. "A Comprehensive Analysis of Online and Offline Energy Management Approaches for Optimal Performance of Fuel Cell Hybrid Electric Vehicles," Energies, MDPI, vol. 16(8), pages 1-33, April.

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