IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i18p4952-d1751838.html
   My bibliography  Save this article

Optimization Design and Experimental Verification of the Hydrogen-Powered Self-Propelled Plant Protection Machine

Author

Listed:
  • Liyou Xu

    (College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
    State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, China)

  • Shuailong Hou

    (College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China)

  • Yanying Li

    (College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
    State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, China)

  • Shenghui Lei

    (College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
    State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, China)

  • Mengnan Liu

    (College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
    State Key Laboratory of Intelligent Agricultural Power Equipment, Luoyang 471039, China
    YTO Group Corporation R&D Center, Luoyang 471039, China)

Abstract

The design objectives for the overall parameters of the hydrogen-powered self-propelled plant protection machine are multiple, and the constraints are complex, making it difficult for single-objective optimization methods to achieve the optimal design. This paper designed the objective function with the goal of optimizing the full-cycle cost and system volume of the energy system. By analyzing the structural characteristics of the power system of the self-propelled plant protection machine, the optimization parameters were determined. A constraint model was developed by studying the operational performance of the self-propelled plant protection machine. The multi-objective particle swarm optimization algorithm was used to derive the multi-objective optimization algorithm for the power system parameters of the hydrogen-powered self-propelled plant protection machine. Parameter optimization and dynamic simulation were carried out using the Matlab/Simulink (2023a) platform, and the results of the designed optimization scheme were compared with the single-objective optimization scheme: the full-cycle cost and system volume decreased by 15.8% and 17.6%, respectively. Both optimization schemes are capable of meeting the plant protection operation load requirements. The fuel cell output efficiency and battery efficiency increased by 15.3% and 10.1%, respectively. The hydrogen consumption of the fuel cell, the equivalent hydrogen consumption of the battery, and the equivalent hydrogen consumption of the system decreased by 10.5%, 13.8%, and 10.8%, respectively. The design conducted performance tests on the prototype of the hydrogen-powered plant protection machine, and the results showed that the operational performance indicators, system equivalent hydrogen consumption, and simulation values had an absolute mean error of 2.418, verifying the optimization method.

Suggested Citation

  • Liyou Xu & Shuailong Hou & Yanying Li & Shenghui Lei & Mengnan Liu, 2025. "Optimization Design and Experimental Verification of the Hydrogen-Powered Self-Propelled Plant Protection Machine," Energies, MDPI, vol. 18(18), pages 1-20, September.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:18:p:4952-:d:1751838
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/18/4952/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/18/18/4952/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:18:p:4952-:d:1751838. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.