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基于遗传算法的机液传动系统参数匹配研究

朱镇1, 蔡英凤1, 陈龙1, 夏长高2, 施德华1   

  1. 1.江苏大学汽车工程研究院,镇江市 212013；2. 江苏大学汽车与交通工程学院,镇江市 212013
  • 出版日期:2019-03-05 发布日期:2019-03-05
  • 基金资助:
     

Parameters matching study on hydro-mechanical transmission system based on genetic algorithm

    

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  • Online:2019-03-05 Published:2019-03-05
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摘要： 多功能机液复合传动装置可使用不同传动方式实现平稳起步、无级调速和快速驶离的功能。本文以一款具有自主知识产权的机液复合传动变速箱为研究对象，进行运动学、动力学和能量管理分析，确定装配方案和基本参数。采用基于Pareto最优原理的多目标遗传算法研究传动系统的参数匹配问题，包括：确定设计变量，选择优化目标，施加约束条件等。建立基于modeFRONTIER的传动系统目标优化模型，分别以爬坡度和燃油消耗率为动力性和经济性目标函数，使用实验设计与优化算法相结合的方法对多目标遗传算法进行全局搜索以寻求最优解。计算表明：爬坡度（o）平均值为27.259，95%置信区间为[26.358，28.161]，Pareto最优解为27.931；燃油消耗率（g/kW·h）平均值为208.876，95%置信区间为[208.622，209.130]，Pareto最优解为206.760。结果表明：动力性和燃油经济性此消彼长，可根据实际要求选取优化解。随着优化迭代步数的增加，爬坡度和燃油消耗率两个目标值都将在一个小范围内收敛，且Pareto最优解的设计变量很好地满足了传动系统的匹配要求。

关键词: 机液复合传动, 能量管理, Pareto最优原理, 参数匹配, 目标函数

Abstract: Multifunctional hydro-mechanical composite transmission devices can realize smooth start, stepless speed regulation and quick departure by different transmission modes. This paper takes a hydro-mechanical composite transmission case with independent intellectual property rights as study object, carries out analysis on kinematics, dynamics and energy management, confirms assembly schemes and basic parameters. Multiobjective genetic algorithm based on Pareto optimal principle is used to study transmission system parameters matching problem, includes determination of design variables, choice of optimization targets, imposition of constraint conditions, and so on. Objective optimization model of transmission system based on modeFRONTIER is established, climbing degree and fuel consumption rate are chosen as objective functions of dynamic performance and fuel economy performance respectively, DOE and optimization algorithm are combined to seek the optimal solution by the global search of multiobjective genetic algorithm. Calculation results show that climbing degree arithmetic mean is 27.259, 95% confidence interval is [26.358，28.161], and Pareto optimal solution is 27.931; fuel consumption rate arithmetic mean is 208.876, 95% confidence interval is [208.622，209.130], and Pareto optimal solution is 206.760. The results show that dynamic performance increase with the decrease of fuel economy performance, so the optimal solution can be chosen according to the actual requirements. As optimal iterative steps increase, the two target values, climbing degree and fuel consumption rate will both convergence in a small scale, and the design variables of Pareto optimal solution well satisfy the matching requirement of transmission system.

Key words: hydro-mechanical composite transmission, energy management, Pareto optimal principle, parameters matching, objective functions

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