• CN:11-2187/TH
  • ISSN:0577-6686

机械工程学报 ›› 2026, Vol. 62 ›› Issue (4): 296-308.doi: 10.3901/JME.260126

• 运载工程 • 上一篇    

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基于粒子群法的山地齿轨车辆悬挂多参数多目标优化

张海涛1, 陈再刚1, 杨国军1, 陈志辉1,2, 陈新1, 杨吉忠2   

  1. 1. 西南交通大学轨道交通运载系统全国重点实验室 成都 610031;
    2. 中铁二院工程集团有限责任公司科学技术研究院 成都 610031
  • 收稿日期:2025-02-17 修回日期:2025-09-07 发布日期:2026-04-02
  • 作者简介:张海涛,男,2000年出生。主要研究方向为车辆系统动力学及多参数优化。E-mail:haitaozhang99@163.com
    陈再刚(通信作者),男,1984年出生,博士,研究员,博士研究生导师。主要研究方向为机械传动系统动力学、车辆系统动力学、故障诊断与信号处理、振动测试与分析。E-mail:zgchen@home.swjtu.edu.cn
  • 基金资助:
    国家自然科学基金优秀青年(521122502)和深海勇士号能力提升及科学应用(2022YFC2805501)资助项目。

Multi-parameter and Multi-objective Optimization of Mountain Rack Vehicle Suspension Based on Particle Swarm Optimization

ZHANG Haitao1, CHEN Zaigang1, YANG Guojun1, CHEN Zhihui1,2, CHEN Xin1, YANG Jizhong2   

  1. 1. State Key Laboratory of Rail Transit Vehicle System, Southwest Jiaotong University, Chengdu 610031;
    2. Scientific Research Institute, China Railway Eryuan Engineering Group Co., Ltd., Chengdu 610031
  • Received:2025-02-17 Revised:2025-09-07 Published:2026-04-02

摘要: 齿轨列车由于其强大的爬坡能力而被广泛应用于山地轨道交通领域。齿轨列车在坡道运行时主要以齿轮齿条啮合提供驱动力,由于齿条制造和安装误差、线路不均匀沉降等因素影响,齿轮齿条啮合动态作用加剧,直接影响齿轨列车乘坐舒适性和安全性。为了提升齿轨车辆爬坡运行时的动态性能,开展基于粒子群法的山地齿轨车辆悬挂多参数多目标优化研究。首先,基于车辆-轨道耦合动力学与齿轮传动系统动力学理论,建立考虑轮轨接触和齿轮齿条啮合激励影响的齿轨车辆-轨道耦合仿真分析模型,并通过现场试验验证了模型的准确性;其次,通过最优拉丁超立方采样生成悬挂参数矩阵并进行方差分析探究悬挂参数敏感性;最后,采用径向基神经网络代理模型与粒子群优化算法对齿轨车辆悬挂参数进行优化。研究结果表明,齿轨车辆悬挂参数交互效应对动力学的敏感性较小,调整单个参数对动力学指标的优化更为直接有效;适当增大齿轨车辆一系垂向阻尼并减小一系垂向刚度可有效提高车辆平稳性和安全性;提出的优化方法能够有效对齿轨车辆悬挂系统寻优,在10~35 km/h的速度范围内都能够有效优化车辆安全性和平稳性。

关键词: 齿轨车辆动力学, 悬挂系统, 敏感性分析, 代理模型, 多目标优化

Abstract: The rack train is widely used in mountain rail transportation due to its strong climbing ability. The gear-rack meshing force is the main power source when the train runs on the ramp. Due to the installation error of the racks and the impact of the line, the gear-rack meshing force is becoming more intensified, which affects the wheel-rail force and aggravates the vibration of the car body. Therefore, the ride comfort and safety of the rack train running on the ramp are reduced. To optimize the ride comfort and safety of the rack train, firstly, based on the theory of vehicle-track coupled dynamics and gear transmission system dynamics, a rack vehicle-track coupling model considering the influence of wheel-rail contact and gear-rack meshing excitation is established, and the accuracy of the model is verified by the experimental validation. Secondly, the suspension parameter matrix is generated by the optimal Latin hypercube sampling and the sensitivity of suspension parameters is explored by the variance analysis. Finally, the Radial Basis Function Neural Network surrogate model and particle swarm optimization algorithm are used to optimize the suspension parameters of the rack train. The simulated results indicate that the interaction effects of the suspension parameters have a minimal sensitivity on the dynamics, making the optimization of dynamic indicators more direct and effective when adjusting individual parameters. Properly increasing the vertical primary damping of the rack vehicle and reducing the vertical primary stiffness can effectively improve the stability and safety of the vehicle. This optimization method effectively identifies the optimal configuration for the suspension system of the rack vehicle, significantly enhancing the safety and stability within a speed range of 10 to 35 km/h.

Key words: rack vehicle dynamic, suspension system, sensitivity analysis, surrogate model, multi-objective optimization

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