吉林大学学报(工学版) ›› 2024, Vol. 54 ›› Issue (5): 1214-1220.doi: 10.13229/j.cnki.jdxbgxb.20221577

• 车辆工程·机械工程 • 上一篇    

粒子群算法下汽车机械式自动变速系统参数多目标优化

陈涛1(),周志刚2,雷楠南1   

  1. 1.河南科技大学 应用工程学院,河南 三门峡 471023
    2.河南科技大学 车辆与交通工程学院,河南 洛阳 471023
  • 收稿日期:2022-12-09 出版日期:2024-05-01 发布日期:2024-06-11
  • 作者简介:陈涛(1966-),男,副教授,博士.研究方向,机械设计,逆向工程.E-mail:ctao202200@163.com
  • 基金资助:
    国家自然科学基金青年基金项目(51805149);河南高校重点科研项目(22B460021)

Multi-objective optimization of parameters of automotive mechanical automatic transmission system based on particle swarm optimization

Tao CHEN1(),Zhi-gang ZHOU2,Nan-nan LEI1   

  1. 1.College of Applied Engineering,Henan University of Science And Technology,Sanmenxia 471023,China
    2.School of Vehicle and Traffic Engineering,Henan University of Science and Technology,Luoyang 471023,China
  • Received:2022-12-09 Online:2024-05-01 Published:2024-06-11

摘要:

汽车机械式自动变速系统难以同时满足低能耗、高动力的运行需求,为提升变速系统运行性能,提出基于粒子群算法的汽车机械式自动变速系统参数多目标优化。该方法首先学习并分析汽车整体动力模型以及电机效率,之后依据汽车在行驶中的最高速度、加速度性能以及爬坡性能确立目标函数,最后利用粒子群算法求解目标函数最优解,利用汽车在行驶过程中的惯性权重使全局搜索能力达到平衡状态,基于学习因子实现粒子自动寻优,实现汽车机械式自动变速系统参数多目标优化。实验结果表明:本文方法能耗低、运行效率高且拥有良好的动力性能,能有效提升汽车机械式自动变速系统的运行性能,对汽车的无延迟变速具有一定的促进作用。

关键词: 粒子群算法, 自动变速系统, 多目标优化, 轮毂电机, 目标函数

Abstract:

Auto mechanical automatic transmission system can not meet the operation requirements of low energy consumption and high power at the same time. In order to improve the operation performance of the transmission system, a multi-objective optimization of auto mechanical automatic transmission system parameters based on particle swarm optimization algorithm is proposed. This method first learns and analyzes the overall dynamic model of the vehicle and the motor efficiency, then establishes the objective function according to the maximum speed, acceleration performance and climbing performance of the vehicle during driving, and finally uses particle swarm optimization algorithm to solve the optimal solution of the objective function, uses the inertia weight of the vehicle during driving to make the global search ability reach a balanced state, and realizes automatic particle optimization based on the learning factor, To realize the multi-objective optimization of the parameters of the automotive mechanical automatic transmission system. The experimental results show that the proposed method has low energy consumption, high operating efficiency and good dynamic performance. It can effectively improve the operation performance of the mechanical automatic transmission system of automobiles, and has a certain role in promoting the non delayed transmission of automobiles.

Key words: particle swarm optimization, automatic transmission system, multi objective optimization, hub motor, objective function

中图分类号: 

  • TP391.4

图1

粒子群算法流程图"

图2

两挡变速系统仿真图"

表1

变速系统主要参数"

参数数值
汽车行驶最高速度/(km·h-1120
加速度/(m·s-26
最大爬坡度/%40
主减速器比3.97
发动机额定转速/(r·min-12500
发动机最大转速/(r·min-16000
一挡速比9
二挡速比9

图3

各方法优化后动力性能对比"

图4

各方法优化后的变速运行效率"

表2

各方法优化后能耗对比 (kW·h)"

时间本文方法文献[1]方法文献[2]方法文献[3]方法
1×1031.351.472.351.56
2×1032.573.464.253.42
3×104.627.796.346.79
4×1037.219.8110.669.83
5×1038.9711.4412.3510.24
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