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Fuzzy Adaptive Energy Management Strategy for a Hybrid Agricultural Tractor Equipped with HMCVT

Author

Listed:
  • Zhen Zhu

    (Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Lingxin Zeng

    (Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Long Chen

    (Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

  • Rong Zou

    (School of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China)

  • Yingfeng Cai

    (Automotive Engineering Research Institute, Jiangsu University, Zhenjiang 212013, China)

Abstract

In order to solve the problem of high fuel consumption and poor emission performance in high horsepower tractors, a parallel hybrid tractor system was designed using a dual power source of an engine and motor matched with a hydro-mechanical continuously variable transmission (HMCVT). An equivalent fuel consumption minimization strategy (ECMS) was used for power distribution of this hybrid system. To address the problem of poor adaptability of the equivalence factor to different working cycles in the conventional ECMS, a fuzzy adaptive equivalent fuel consumption minimization strategy (FA-ECMS) was proposed. A fuzzy PI controller based on battery SOC (State of Charge) feedback was designed to adjust the equivalence factor in real time, so as to achieve adaptive control of the equivalence factor. The physical model of the system was built by SimulationX, and the model of the control strategy was built using Matlab/Simulink. Two typical cycles of tractor plowing and road transportation were simulated. Under ECMS, the fuel consumption of the hybrid agricultural tractor was 14.3 L and 1.19 L in one plowing cycle and one transport cycle, respectively, with final battery SOC values of 60.75% and 60.32%, respectively. Under FA-ECMS, the hybrid farm tractor consumed 13.34 L and 1.13 L in one plowing cycle and one transport cycle, respectively, with final battery SOC values of 60.27% and 60.17%, respectively. The results showed that, with the introduction of a fuzzy PI controller to dynamically adjust the equivalence factor, the overall fuel consumption was reduced by 6.71% and 5.04%, respectively, and the battery power maintenance performance was improved. The designed control strategy could achieve a more reasonable power distribution between the engine and motor while maintaining the balance of the battery SOC.

Suggested Citation

  • Zhen Zhu & Lingxin Zeng & Long Chen & Rong Zou & Yingfeng Cai, 2022. "Fuzzy Adaptive Energy Management Strategy for a Hybrid Agricultural Tractor Equipped with HMCVT," Agriculture, MDPI, vol. 12(12), pages 1-21, November.
    • Handle: RePEc:gam:jagris:v:12:y:2022:i:12:p:1986-:d:981558
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    References listed on IDEAS

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    1. Md. Abu Ayub Siddique & Yong-Joo Kim & Seung-Min Baek & Seung-Yun Baek & Tae-Ho Han & Wan-Soo Kim & Yeon-Soo Kim & Ryu-Gap Lim & Yong Choi, 2022. "Development of the Reliability Assessment Process of the Hydraulic Pump for a 78 kW Tractor during Major Agricultural Operations," Agriculture, MDPI, vol. 12(10), pages 1-15, October.
    2. Tian, Xiang & Cai, Yingfeng & Sun, Xiaodong & Zhu, Zhen & Xu, Yiqiang, 2019. "An adaptive ECMS with driving style recognition for energy optimization of parallel hybrid electric buses," Energy, Elsevier, vol. 189(C).
    3. Francesco Mocera & Aurelio Somà, 2020. "Analysis of a Parallel Hybrid Electric Tractor for Agricultural Applications," Energies, MDPI, vol. 13(12), pages 1-16, June.
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    Cited by:

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    2. 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.
    3. Rundong Zhou & Lin Wang & Xiaoting Deng & Chao Su & Song Fang & Zhixiong Lu, 2024. "Research on Energy Distribution Strategy of Tandem Hybrid Tractor Based on the Pontryagin Minimum Principle," Agriculture, MDPI, vol. 14(3), pages 1-17, March.
    4. Junjiang Zhang & Mingyue Shi & Mengnan Liu & Hanxiao Li & Bin Zhao & Xianghai Yan, 2024. "Dual-Source Cooperative Optimized Energy Management Strategy for Fuel Cell Tractor Considering Drive Efficiency and Power Allocation," Agriculture, MDPI, vol. 14(9), pages 1-26, August.
    5. Qian Zhang & Caiqi Hu & Rui Li, 2024. "Research on Distributed Dual-Wheel Electric-Drive Fuzzy PI Control for Agricultural Tractors," Agriculture, MDPI, vol. 14(9), pages 1-19, August.
    6. Piras, M. & De Bellis, V. & Malfi, E. & Novella, R. & Lopez-Juarez, M., 2024. "Hydrogen consumption and durability assessment of fuel cell vehicles in realistic driving," Applied Energy, Elsevier, vol. 358(C).
    7. Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.

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