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

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...

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Bibliographic Details
Published in:Energies (Basel) Vol. 18; no. 18; p. 4952
Main Authors: Xu, Liyou, Hou, Shuailong, Li, Yanying, Lei, Shenghui, Liu, Mengnan
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.09.2025
Subjects:
Adaptability
Agricultural land
Algorithms
Analysis
China
Electric power systems
Energy
experimental verification
Farm machinery
Force and energy
Fuel cells
Hydrogen
Hydrogen as fuel
hydrogen hybrid power
Mathematical optimization
multi-objective optimization method
Optimization
Response time
self-propelled plant protection machine
China
ISSN:1996-1073, 1996-1073
Online Access:Get full text
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Summary: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.
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content type line 14
ISSN:1996-1073
1996-1073
DOI:10.3390/en18184952