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

Liyou Xu, Shuailong Hou, Yanying Li, Shenghui Lei and Mengnan Liu ()
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Liyou Xu: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, 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
Shenghui Lei: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China
Mengnan Liu: College of Vehicle and Traffic Engineering, Henan University of Science and Technology, Luoyang 471003, China

Energies, 2025, vol. 18, issue 18, 1-18

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.

Keywords: hydrogen hybrid power; multi-objective optimization method; experimental verification; self-propelled plant protection machine (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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