Multi-objective optimization of design parameters for tractor hydro-mechanical continuously variable transmissions

The design parameters of the transmission directly affect the vehicle’s dynamics and fuel economy, due to the complexity of the tractor’s working conditions and operating modes, the optimization of the transmission design parameters is more difficult. In this paper, an independently designed hydro-m...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 13261 - 12
Main Authors: Zhu, Zhen, Hou, Rui, Zhang, Hongwei, Wang, Dehai, Chen, Long
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 17.04.2025
Nature Publishing Group
Nature Portfolio
Subjects:
639/166
639/166/988
Agricultural equipment
Algorithms
Energy consumption
Energy efficiency
Experimental design
Fuel economy
Genetic algorithms
Humanities and Social Sciences
Hydro-mechanical continuously variable transmission (HMCVT)
modeFrontier
multidisciplinary
Objective function
Optimization
Pareto optimal solution
Pareto optimum
Powertrain
Science
Science (multidisciplinary)
Working conditions
Pareto optimal solution
Powertrain
modeFrontier
Hydro-mechanical continuously variable transmission (HMCVT)
Optimization
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:The design parameters of the transmission directly affect the vehicle’s dynamics and fuel economy, due to the complexity of the tractor’s working conditions and operating modes, the optimization of the transmission design parameters is more difficult. In this paper, an independently designed hydro-mechanical CVT transmission is taken as the research object, and the transmission design parameters are optimized based on the tractor’s whole life-cycle speed usage rate, and the Multi-Objective Genetic Algorithm(MOGA) is used for optimization and solution. In this paper, the fuel consumption rate and hill climbing degree are taken as the optimization objective function, the parameters that have a greater influence on the optimization objectives are selected as the design variables, and the constraints are determined. A multi-objective genetic algorithm based on the Pareto optimality principle combined with experimental design is used to establish a multi-objective optimization model of the transmission device based on modeFrontier, and a global search for optimality is carried out, and a Pareto optimal solution is finally obtained. The results of the study find the optimal solution under the constraints, reflecting the conflicting characteristics between power and fuel economy. The design variables of the Pareto optimal solution obtained through optimization iterations based on the whole life cycle speed usage rate satisfy the matching requirements of the transmission well.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-89425-y