基于遗传算法的机液传动系统参数匹配研究*

doi:10.19562/j.chinasae.qcgc.2020.01.011

Abstract

Abstract: In this paper, analyses on the kinematics, kinetics and energy management of a hydro-mechanical compound transmission are carried out with its assembly schemes and basic parameters determined. Multi-objective genetic algorithm based on Pareto optimal principle is used to study the matching issue of transmission system, including the selection of optimization objectives and the determination of design variables and constraints and so on. Multi-objective optimization model of transmission system is established based on modeFRONTIER, climbing slope and specific fuel consumption are chosen as objective functions for power performance and fuel economy respectively, and Multi-objective genetic algorithm is adopted combined with the design of experiment, to conduct global search on the model for seeking the optimum solution. The results show that the arithmetic mean of climbing slope is 27.26°, with a 95% confidence interval of [26.36°,28.16°] and a Pareto optimal solution of 27.93°; the arithmetic mean of specific fuel consumption is 208.88 g/(kW·h), with a 95% confidence interval of [208.62,209.13]/g/(kW·h) and a Pareto optimal solution of 206.76 g/(kW·h). As the iterative steps of optimization increase, both objectives, i.e. climbing slope and specific fuel consumption will convergence in a small range, and the Pareto optimal solution of design variables well meet the matching requirements of transmission system

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

Zhu Zhen, Cai Yingfeng, Chen Long, Xia Changgao, Shi Dehua. A Study on Parameter Matching of Hydro-mechanicalTransmission System Based on Genetic Algorithm[J].Automotive Engineering, 2020, 42(1): 74-80.

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A Study on Parameter Matching of Hydro-mechanicalTransmission System Based on Genetic Algorithm

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