基于混合粒子群算法的组合式变速箱传动比优化研究

doi:10.16182/j.issn1004731x.joss.19-0655

摘要/Abstract

摘要： 针对组合式变速箱传动比分配难以得到最优方案的问题,提出基于混合粒子群算法的组合式多档位变速箱的传动比优化方法。基于多目标粒子群算法,引入具有自我更新机制的领导种群,构成混合粒子群算法。以各段单级变速的传动比为变量,结合传动链布局,以驱动功率损失率、比油耗损失率等为优化目标,以理论车速等为约束条件,建立多目标优化模型,并与非支配遗传算法-Ⅱ、多目标粒子群算法的优化结果进行了对比。结果表明：采用混合粒子群算法可实现驱动功率损失率下降17.47%和比油耗损失率下降35.12%,具有良好的应用价值。

关键词: 组合式变速箱, 传动比优化, 混合粒子群算法, 多目标优化

Abstract: Aiming at the difficulty to obtain the optimal solution for the transmission ratio distribution of combined transmission, an optimization method for the transmission ratio of the combined multi-speed transmission based on the hybrid particle swarm optimization algorithm is proposed. Based on the multi-objective particle swarm algorithm, a leader population with a self-renewal mechanism is introduced to form a hybrid particle swarm algorithm. A multi-objective optimization model is established by taking the transmission ratio of each stage of single-speed transmission as a variable, combining the transmission chain layout, taking the driving power loss rate, specific fuel consumption loss rate, etc. as the optimization objective and the theoretical vehicle speed as the constraints. The optimization results are compared with those of the NSGA-Ⅱand MOPSO algorithm. The results show that the hybrid particle swarm optimization algorithm can reduce the driving power loss rate by 17.47% and the specific fuel consumption loss rate by 35.12%, which has good application value.

Key words: combined gearbox, transmission ratio optimization, hybrid particle swarm optimization algorithm, multi-objective optimization

中图分类号:

TP202

汪润鸿, 王红军, 邹湘军, 曾泽钦, 李慧, 黄钊丰, 刘伟良. 基于混合粒子群算法的组合式变速箱传动比优化研究[J]. 系统仿真学报, 2021, 33(4): 825-836.

Wang Runhong, Wang Hongjun, Zou Xiangjun, Zeng Zeqin, Li Hui, Huang Zhaofeng, Liu WeiLiang. Combined Gearbox Transmission Ratio Optimization Research Based on Hybrid Particle Swarm[J]. Journal of System Simulation, 2021, 33(4): 825-836.

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