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Research on Energy Management Strategy of Fuel Cell Electric Tractor Based on Multi-Algorithm Fusion and Optimization

Author

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  • Hongtu Yang

    (School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China
    Department of Vehicle Engineering, Changzhou Vocational Institute of Mechatronic Technology, Changzhou 213164, China)

  • Yan Sun

    (School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Changgao Xia

    (School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Hongdang Zhang

    (Department of Vehicle Engineering, Changzhou Vocational Institute of Mechatronic Technology, Changzhou 213164, China)

Abstract

To solve the serious pollution problems of traditional fuel tractors and the short continuous operation time of pure electric tractors, a hybrid tractor with fuel cell as the primary power source and battery as the auxiliary power source is proposed. A novel energy management strategy was also designed, which integrates thermostat control strategy, power following strategy, and fuzzy logic control. The energy management strategy utilizes the advantages of different algorithms and realizes the rational distribution of fuel cell and battery output power. The system economy and fuel cell durability are improved by the tabu search algorithm. The simulation results show that the proposed energy management strategy can work well in different SOC states and reduce the fuel cell’s power fluctuations. The tractor is equipped with 960 g of hydrogen, the initial state of charge (SOC) is 90%, and it can operate continuously for 2.65 h.

Suggested Citation

  • Hongtu Yang & Yan Sun & Changgao Xia & Hongdang Zhang, 2022. "Research on Energy Management Strategy of Fuel Cell Electric Tractor Based on Multi-Algorithm Fusion and Optimization," Energies, MDPI, vol. 15(17), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:17:p:6389-:d:903933
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Junjiang & Feng, Ganghui & Yan, Xianghai & He, Yundong & Liu, Mengnan & Xu, Liyou, 2024. "Cooperative control method considering efficiency and tracking performance for unmanned hybrid tractor based on rotary tillage prediction," Energy, Elsevier, vol. 288(C).
    2. Li, Xianzhe & Liu, Mengnan & Hu, Chenming & Yan, Xianghai & Zhao, Sixia & Zhang, Mingzhu & Xu, Liyou, 2024. "Parameters collaborative optimization design and innovation verification approach for fuel cell distributed drive electric tractor," Energy, Elsevier, vol. 292(C).
    3. Ugnė Koletė Medževeprytė & Rolandas Makaras & Vaidas Lukoševičius & Sigitas Kilikevičius, 2023. "Application and Efficiency of a Series-Hybrid Drive for Agricultural Use Based on a Modified Version of the World Harmonized Transient Cycle," Energies, MDPI, vol. 16(14), pages 1-16, July.
    4. Hyoung-Jong Ahn & Young-Jun Park & Su-Chul Kim & Chanho Choi, 2023. "Theoretical Calculations and Experimental Studies of Power Loss in Dual-Clutch Transmission of Agricultural Tractors," Agriculture, MDPI, vol. 13(6), pages 1-16, June.
    5. Valerio Martini & Francesco Mocera & Aurelio Somà, 2022. "Numerical Investigation of a Fuel Cell-Powered Agricultural Tractor," Energies, MDPI, vol. 15(23), pages 1-19, November.

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