Zhu Zhen, Hou Rui, Zhang Hongwei, Wang Dehai, Chen Long
Automotive Engineering Research Institute, Jiangsu University, Zhenjiang, 212013, Jiangsu, China.
National Key Laboratory of Special Vehicle Design and Manufacturing Integration Technology, Baotou, 014030, Inner Mongolia, China.
Sci Rep. 2025 Apr 17;15(1):13261. doi: 10.1038/s41598-025-89425-y.
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.
变速器的设计参数直接影响车辆的动力学性能和燃油经济性,由于拖拉机工作条件和运行模式的复杂性,变速器设计参数的优化更加困难。本文以自主设计的液压机械无级变速器为研究对象,基于拖拉机全生命周期速度使用率对变速器设计参数进行优化,并采用多目标遗传算法(MOGA)进行优化求解。本文以燃油消耗率和爬坡能力为优化目标函数,选取对优化目标影响较大的参数作为设计变量,并确定约束条件。基于帕累托最优原理结合实验设计的多目标遗传算法,利用modeFrontier建立变速器装置的多目标优化模型,进行全局最优搜索,最终得到帕累托最优解。研究结果在约束条件下找到了最优解,体现了动力性与燃油经济性之间的矛盾特性。基于全生命周期速度使用率通过优化迭代得到的帕累托最优解的设计变量很好地满足了变速器的匹配要求。