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Research on Energy Management Strategy of Fuel Cell Vehicle Based on Multi-Dimensional Dynamic Programming

Author

Listed:
  • Yanwei Liu

    (School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510640, China)

  • Jiansheng Liang

    (School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510640, China)

  • Jiaqing Song

    (School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou 510640, China)

  • Jie Ye

    (School of Mechatronics Engineering, Foshan University, Foshan 528225, China)

Abstract

The powertrain of a fuel cell vehicle typically consists of two energy sources: a proton electrolyte membrane fuel cell (PEMFC) stack and a battery package. In this paper, multi-dimensional dynamic programming (MDDP) is used to solve the energy management strategy (EMS) of fuel cell hybrid powertrain. This study built a fuel cell hybrid powertrain model, in which the battery model is built based on the Thevenin equivalent circuit. In order to improve the calculating efficiency and maintain the accuracy of the algorithm, the state variables in each stage are divided into primary and secondary. In the reverse solution process, the corresponding relationship between the multi state variables grid and the optimal cumulative function has been changed from three-dimensional to two-dimensional. The EMS based on MDDP is applied to component sizing of a commercial vehicle. Simulations were conducted using MATLAB under the C-WTVC working condition. By analyzing the fuel economy and system durability, the optimal component combination of comprehensive performance is obtained. Compared with the EMS based on dynamic programming (DP), the proposed method effectively improves the calculation accuracy: the hydrogen consumption can be reduced by 3.10%, and the durability of the fuel cell and battery can be improved by 1.08% and 0.13%, respectively.

Suggested Citation

  • Yanwei Liu & Jiansheng Liang & Jiaqing Song & Jie Ye, 2022. "Research on Energy Management Strategy of Fuel Cell Vehicle Based on Multi-Dimensional Dynamic Programming," Energies, MDPI, vol. 15(14), pages 1-20, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:14:p:5190-:d:865051
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    References listed on IDEAS

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    1. Yanwei Liu & Zhenye Li & Yuzhong Chen & Kegang Zhao, 2020. "A Novel Fuel-Cell Electric Articulated Vehicle and Its Drop-and-Pull Transport System," Energies, MDPI, vol. 13(14), pages 1-17, July.
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    Cited by:

    1. Yuguo Xu & Enyong Xu & Weiguang Zheng & Qibai Huang, 2023. "Hierarchical Model-Predictive-Control-Based Energy Management Strategy for Fuel Cell Hybrid Commercial Vehicles Incorporating Traffic Information," Sustainability, MDPI, vol. 15(17), pages 1-21, 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.
    3. Enas Taha Sayed & Abdul Ghani Olabi & Abdul Hai Alami & Ali Radwan & Ayman Mdallal & Ahmed Rezk & Mohammad Ali Abdelkareem, 2023. "Renewable Energy and Energy Storage Systems," Energies, MDPI, vol. 16(3), pages 1-26, February.
    4. Enyong Xu & Mengcheng Ma & Weiguang Zheng & Qibai Huang, 2023. "An Energy Management Strategy for Fuel-Cell Hybrid Commercial Vehicles Based on Adaptive Model Prediction," Sustainability, MDPI, vol. 15(10), pages 1-20, May.

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