Optimization of Wheelset Tread for High-Speed Trains Considering Curve Passing Performance of LMA/CHN60N Wheel-Track
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摘要:
为提高动车组列车在曲线路段的通过性能,从而减小轮对磨耗,延长服役寿命,以LMA/CHN60N轮-轨组合为研究对象,设置列车通过曲线轨道段时车轮踏面与轨道密切接触的6个尺寸为设计变量,将两侧轮轨间的最大横移量、最大爬升量与最大接触应力定义为目标函数,对车轮踏面尺寸进行响应面优化设计,并对优化方案进行瞬态动力学分析. 研究结果表明:与现有动车组轮对相比,优化后外侧车轮的最大横移量、最大爬升量与最大接触应力分别降低1.74%、1.34%与4.49%,内侧车轮的最大横移量、最大爬升量与最大接触应力分别降低0.41%,1.53%与3.92%;在保证列车其他性能的前提下,优化方案提高了车辆在曲线轨道段的通过性能,可降低轮对磨耗,且直线通过性能、安全性、平稳性及耐久性指标均在允许范围内,从而延长其服役寿命.
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关键词:
- 动车组轮对 /
- 车轮踏面 /
- 响应面优化设计 /
- 曲线通过性能 /
- LMA/CHN60N轮-轨
Abstract:To improve the passing performance of high-speed trains on curved sections, reduce wheelset wear, and extend service life, the LMA/CHN60N wheel-track combination was taken as the research object. Six dimensions of the wheel tread in close contact with the track when the train passes through the curved track section were set as design variables, and the maximum lateral displacement, maximum climb, and maximum contact stress between the wheel and track on both sides were defined as objective functions. The response surface optimization design of the wheel tread dimensions was conducted, and the transient dynamics analysis of the optimization scheme was performed. The results indicate that compared with existing wheelsets of high-speed trains, the maximum lateral displacement, maximum climb, and maximum contact stress of the optimized outer wheels decrease by 1.74%, 1.34%, and 4.49%, respectively, and the maximum lateral displacement, maximum climb, and maximum contact stress of the inner wheels decrease by 0.41%, 1.53%, and 3.92%, respectively. Under the premise of ensuring other performances of the train, the optimization scheme improves the passing performance of the vehicle on curved track sections and can reduce wheelset wear; moreover, the indicators of straight passing performance, safety, smoothness, and durability are all within allowable ranges, thereby extending its service life.
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表 1 国内外典型动车组列车
Table 1. Typical high-speed trains in China and abroad
国家 动车组列车类型 轮对踏面类型 日本 700系 圆弧形 德国 ICE3 圆弧形 法国 TGV-2N 锥形 美国 M-479 AAR型 中国 CRH1、CRH2 LMA型 CRH3 S1002CN型 CRH5 XP55型 表 2 车轮、车轴与轨道的材料参数
Table 2. Material parameters of wheels, axles, and tracks
类别 材料 密度ρ/(kg•m−3) 弹性模量E/GPa 泊松比v 屈服强度σ/MPa 车轮 ER8 7 850 206 0.3 540 车轴 EA4T 7 850 212 0.28 830 轨道 U71MnG 7 800 210 0.3 400 表 3 目标函数及其权重排序
Table 3. Objective functions and their weight rankings
评价指标 目标函数 权重
排序轮轨间
横移量外侧轮轨间最大横移量$ a_{\max }^{\text{OH}} $/mm 1 内侧轮轨间最大横移量$ a_{\max }^{\text{IH}} $/mm 2 轮轨间
爬升量外侧轮轨间最大爬升量$ a_{\max }^{\text{OL}} $/mm 3 内侧轮轨间最大爬升量$ a_{\max }^{\text{IL}} $/mm 4 轮轨间
接触应力外侧轮轨间最大接触应力$ F_{\max }^{\text{O}} $/MPa 5 内侧轮轨间最大接触应力$ F_{\max }^{\text{I}} $/MPa 6 表 4 设计变量优化前后对比
Table 4. Comparison of design variables before and after optimization
设计变量 优化前 优化后 x1/mm 32 30.514 67 x2/mm 30 31.259 1 x3/mm 12 10.806 x4/(°) 70 73.269 x5/mm 28 26.993 4 x6/mm 90 91.412 表 5 轮轨间接触斑优化前后对比
Table 5. Comparison of contact spots between wheel and rail before and after optimization
接触斑 项目 形状 面积/mm2 外侧接触斑 优化前 
62.43 优化后 
63.643 内侧接触斑 优化前 
133.506 优化后 
137.92 表 6 各目标函数优化前后对比
Table 6. Comparison of objective functions before and after optimization
目标函数 优化前 优化后 变率% $ a_{\max }^{\text{OH}} $/mm 0.382 34 0.375 70 −1.74 $ a_{\max }^{\text{OL}} $/mm −0.196 20 −0.198 82 −1.34 $ a_{\max }^{\text{IH}} $/mm 0.288 34 0.287 17 −0.41 $ a_{\max }^{\text{IL}} $/mm −0.271 42 −0.267 28 −1.53 $ F_{\max }^{\text{O}} $/MPa 58.01900 55.41500 −4.49 $ F_{\max }^{\text{I}} $/MPa 52.11600 50.07300 −3.92 表 7 轮对优化后第7 ~ 12阶自由模态的频率
Table 7. Frequencies of 7th–12th order free modes after wheelset optimization
阶数 频率/Hz 7 81.219 8 97.364 9 97.364 10 191.88 11 191.88 12 345.43 表 8 客车平稳性等级
Table 8. Smoothness levels of passenger trains
平稳性等级 乘客感受 Sperling指标 1级 优 <2.5 2级 良好 2.5 ~ 2.75 3级 合格 2.75 ~ 3.0 表 9 优化方案除6个目标函数外其他性能的分析结果
Table 9. Analysis results of other performances of optimization scheme excluding six objective functions
性能指标 具体参数 允许范围/原方案分析结果 优化方案的分析结果 是否满足要求/
优于原方案外侧轮轨/横向振动 内侧轮轨/垂向振动 直线性能 横移量/mm <0.5 0.427 67 0.350 77 是 爬升量/mm <0.5 −0.432 90 −0.435 80 是 最大应力/MPa <540 65.577 66.768 是 安全性 脱轨系数 ≤1.0 0.4 0.35 是 倾覆系数 ≤0.8 0.262 9 是 平稳性 平稳性指数 <2.5 0.835 2 0.979 3 是 耐久性 表面疲劳因子 0.321 822(外)
0.321 432(内)0.321 661 0.321 134 是 磨耗体积/mm2 1.431 × 10−7(外)
4.020 × 10−7(内)1.407 × 10−7 4.055 × 10−7 是 磨耗指数 871.083 186.271 5 是 -
[1] 逯万春, 姜培斌, 凌亮, 等. 基于KCF-Hash-Match目标跟踪算法的高速列车车轮横向晃动识别方法[J]. 机械工程学报, 2023, 59(24): 223-230.Lu Wanchun, Jiang Peibin, Ling Liang, et al. KCF-hash-match target tracking algorithm for identifying wheel lateral sway of high-speed train[J]. Journal of Mechanical Engineering, 2023, 59(24): 223-230. [2] 程翔, 朱禹熹, 贾林. 基于多尺度可分离蒸馏网络的列车轮对踏面缺陷检测算法[J]. 铁道科学与工程学报, 2024, 21(11): 4789-4803. doi: 10.19713/j.cnki.43-1423/u.T20240190Cheng Xiang, Zhu Yuxi, Jia Lin. Train wheel tread defect detection algorithm based on multi-scale separable distillation network[J]. Journal of Railway Science and Engineering, 2024, 21(11): 4789-4803. doi: 10.19713/j.cnki.43-1423/u.T20240190 [3] 刘文朋, 杨绍普, 刘泽潮, 等. 变转速工况下基于快速谱平均峭度图的列车轮对轴承故障诊断[J]. 铁道学报, 2024, 46(5): 38-47. doi: 10.3969/j.issn.1001-8360.2024.05.005Liu Wenpeng, Yang Shaopu, Liu Zechao, et al. Fault diagnosis of train wheelset bearings based on fast average kurtogram under variable speed conditions[J]. Journal of the China Railway Society, 2024, 46(5): 38-47. doi: 10.3969/j.issn.1001-8360.2024.05.005 [4] 王文静, 闫瑞国, 丁然, 等. 高速列车智能轮对应力谱测试及车轴裂纹扩展寿命分析[J]. 中南大学学报(自然科学版), 2022, 53(5): 1955-1964.Wang Wenjing, Yan Ruiguo, Ding Ran, et al. Intelligent wheelset stress spectrum testing and axle crack propagation life analysis for high-speed trains[J]. Journal of Central South University (Science and Technology), 2022, 53(5): 1955-1964. [5] 邓飞跃, 蔡毓龙, 王锐, 等. 基于卷积与Transformer融合框架的列车轮对轴承损伤识别方法[J]. 工程科学学报, 2024, 46(10): 1834-1844.Deng Feiyue, Cai Yulong, Wang Rui, et al. Train wheelset bearing damage identification method based on convolution and transformer fusion framework[J]. Chinese Journal of Engineering, 2024, 46(10): 1834-1844. [6] 杨能普, 周苗, 王文昆, 等. 基于R-P图像注意融合网络的列车轮对踏面缺陷识别[J]. 铁道科学与工程学报, 2023, 20(12): 4811-4822. doi: 10.19713/j.cnki.43-1423/u.T20230152Yang Nengpu, Zhou Miao, Wang Wenkun, et al. Wheelset tread defect recognition based on R-P image attention fusion network[J]. Journal of Railway Science and Engineering, 2023, 20(12): 4811-4822. doi: 10.19713/j.cnki.43-1423/u.T20230152 [7] Wu J Y, Li Y L, Jia L M, et al. Semi-supervised fault diagnosis of wheelset bearings in high-speed trains using autocorrelation and improved flow Gaussian mixture model[J]. Engineering Applications of Artificial Intelligence, 2024, 132: 107861. doi: 10.1016/j.engappai.2024.107861 [8] Yang J W, Sun R T, Yao D C, et al. Early faint fault diagnosis of wheelset axlebox bearings in urban rail trains based on ICiSSA-MOMEDA[J]. Measurement Science and Technology, 2024, 35(2): 026107. doi: 10.1088/1361-6501/ad0880 [9] Yang X X, Tao G Q, Wen Z F. Causes and evolution of asymmetric polygonal wear of metro train wheelsets[J]. Wear, 2023, 530: 205036. doi: 10.1016/j.wear.2023.205036 [10] Sun Z H, Zheng C X, Sun X Q, et al. Dual multi-objective optimization design method for compliant guide mechanism[J]. Structural and Multidisciplinary Optimization, 2024, 67(5): 75. doi: 10.1007/s00158-024-03793-z [11] An W G, Lin T Y, Wang S G. Optimal structural design for a certain near-space composite propeller of airship using adaptive region division blending model[J]. Chinese Journal of Aeronautics, 2024, 37(5): 301-316. doi: 10.1016/j.cja.2023.11.018 [12] Yang P, Sun L Y, Zhang M L, et al. A lightweight optimal design method for magnetic adhesion module of wall-climbing robot based on surrogate model and DBO algorithm[J]. Journal of Mechanical Science and Technology, 2024, 38(4): 2041-2053. doi: 10.1007/s12206-024-0334-3 [13] 李晨杰. 轨缝处的轮轨接触力学分析及优化设计[D]. 大连: 大连交通大学, 2022. [14] 唐彦玲. 重载曲线轨道钢轨廓形优化设计[D]. 成都: 西南交通大学, 2020. [15] 翁涛涛. 高速道岔磨耗分析及打磨廓形优化设计[D]. 南昌: 华东交通大学, 2023. [16] 张卫华. 动车组总体与转向架[M]. 北京: 中国铁道出版社, 2011. [17] 王健, 马晓川, 陈嘉胤, 等. 高速铁路CHN60N钢轨与不同车轮踏面匹配性能研究[J]. 铁道学报, 2017, 39(12): 94-101. doi: 10.3969/j.issn.1001-8360.2017.12.013Wang Jian, Ma Xiaochuan, Chen Jiayin, et al. Study of matching performance of CHN60N rail with different wheel treads in high-speed railway[J]. Journal of the China Railway Society, 2017, 39(12): 94-101. doi: 10.3969/j.issn.1001-8360.2017.12.013 [18] 李媛媛. 高速列车轮对不同工况下应力及疲劳强度分析[D]. 兰州: 兰州交通大学, 2022. [19] 国家铁路局. 铁路线路设计规范: TB 10098—2017[S]. 北京: 中国铁道出版社, 2017. [20] 康熙. 轮对偏心引起铁路车轮非圆化的形成机制及其影响研究[D]. 成都: 西南交通大学, 2022. [21] 张曙光. 高速列车设计方法研究[M]. 北京: 中国铁道出版社, 2009. [22] 袁硕. 某动车转向架构架结构分析及优化[D]. 大连: 大连交通大学, 2023. [23] 铁道车辆动力学性能评定和试验鉴定规范 GB/T 5599-1985 [S]. 北京: 国家铁路局, 1985: 3-4. [24] 肖乾, 罗志翔, 李超. CHN60/UIC60钢轨廓型下高速列车车轮踏面磨耗对比分析[J]. 润滑与密封, 2018, 43(10): 6-11.Xiao Qian, Luo Zhixiang, Li Chao. Comparison and analysis of wheel profile wear of high speed train with CHN60/UIC60 rail profile[J]. Lubrication Engineering, 2018, 43(10): 6-11. [25] 刘学, 张军, 邹小春, 等. 高速铁路车轮与钢轨型面匹配分析[J]. 中国科技论文, 2020, 15(2): 188-193.Liu Xue, Zhang Jun, Zou Xiaochun, et al. Matching analysis of wheel and rail profile of high-speed railway[J]. China Sciencepaper, 2020, 15(2): 188-193. [26] 白瑾瑜, 曾京, 石怀龙, 等. 抗蛇行减振器对高速列车稳定性的影响[J]. 振动与冲击, 2020, 39(23): 78-83. doi: 10.13465/j.cnki.jvs.2020.23.012Bai Jinyu, Zeng Jing, Shi Huailong, et al. Effects of anti-hunting shock absorber on stability of high-speed train[J]. Journal of Vibration and Shock, 2020, 39(23): 78-83. doi: 10.13465/j.cnki.jvs.2020.23.012 [27] 王宁. 高速铁路站区小半径曲线减磨研究[J]. 铁道建筑, 2017, 57(10): 124-127, 138. doi: 10.3969/j.issn.1003-1995.2017.10.33Wang Ning. Study on rail wear reducing of small radius curve in high speed railway station yard[J]. Railway Engineering, 2017, 57(10): 124-127,138. doi: 10.3969/j.issn.1003-1995.2017.10.33 -
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