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 ORCID:

Chao CHANG

https://orcid.org/0000-0002-9671-6673

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Journal of Zhejiang University SCIENCE  A

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Finite element model updating methodology and application to flexible resonance of high-speed railway vehicles


Author(s):  Chao CHANG, Liang LING, Xiaoyi MA, Fansong LI, Tao LIU, Wanming ZHAI

Affiliation(s):  School of Mechatronics and Vehicle Engineering, East China Jiaotong University, Nanchang 330013, China; more

Corresponding email(s):  liangling@swjtu.edu.cn

Key Words:  High-speed train; Carbody flexible resonance; Finite element (FE); Model updating; Modal frequency


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Chao CHANG, Liang LING, Xiaoyi MA, Fansong LI, Tao LIU, Wanming ZHAI. Finite element model updating methodology and application to flexible resonance of high-speed railway vehicles[J]. Journal of Zhejiang University Science A,in press.Frontiers of Information Technology & Electronic Engineering,in press.https://doi.org/10.1631/jzus.A2400478

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year="in press",
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doi="https://doi.org/10.1631/jzus.A2400478"
}

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%J Journal of Zhejiang University SCIENCE A
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Abstract: 
The flexible resonance phenomenon of a carbody greatly affects the stability and safety of high-speed trains. Therefore, an accurate finite element (FE) model is crucial for establishing a rigid–flexible multi-body dynamics model and revealing the flexible resonance mechanism of high-speed trains. In this paper, we introduced an effective calibration and validation methodology for a carbody FE model of high-speed trains based on experimental modal analysis (EMA). A detailed three-dimensional (3D) carbody FE model that considered practical constraints was developed, and the carbody material parameters were optimized using a genetic algorithm (GA). Based on the updated model, a high-speed railway vehicle–track rigid–flexible coupled dynamics model was established. Results showed excellent agreement between the numerical simulations and field measurements. The proposed method was able to accurately reproduce the carbody flexible resonance phenomenon and elastic modal frequency observed on site.

高速列车整备状态车体有限元模型修正方法与应用研究

作者:昌超1,2,3,凌亮2,马晓毅1,李凡松2,刘涛3,翟婉明2
机构:1华东交通大学,机电与车辆工程学院,中国南昌,330013;2西南交通大学,轨道交通运载系统全国重点实验室,中国成都,610031;3中车长春轨道客车股份有限公司,中国长春,130062
目的:车体柔性共振现象对高速列车的运行稳定性与行车安全具有显著影响。因此,建立精确的有限元(FE)模型对于构建刚柔耦合多体动力学模型并揭示高速列车车体柔性共振机理至关重要。首先,本文提出了一种基于实验模态分析(EMA)的高速列车整备状态车体有限元模型修正策略:构建充分考虑实际约束条件的整备状态精细化车体三位有限元模型,采用遗传算法(GA)结合实验模态数据对模型材料属性参数进行迭代优化。随后,基于更新后的车体有限元模型,构建高速列车车辆-轨道刚柔耦合动力学模型。研究表明:数值仿真结果与现场实测结果高度一致,能够准确再现车体柔性共振现象及其异常抖振频率。该研究工作为高速列车车体有限元模型更新与车体柔性振动机理提供了可参考的理论方法与应用场景。
创新点:1.结合实验模态分析与遗传算法,提出针对高速列车整备状态车体的有限元模型修正方法,实现车体有限元模型材料参数的精准优化;2.通过建立考虑实际约束的精细化三维车体有限元模型,并考虑车下附属设备及连接方式对模态特性的影响,提升模型准确度;3.通过将修正后的车体有限元模型应用于车辆-轨道耦合动力学分析,成功复现车体柔性共振现象,并验证模型在动态响应模拟中的有效性,为车体柔性振动问题的研究提供新的技术路径。
方法:1.构建三维车体有限元模型:将车体铝合金外壳、内部配件及底部设备考虑在内,并采用壳单元、梁单元、质量单元等模拟不同结构,定义材料参数并进行初始模态分析(表1和图5)。2.开展车体模态试验:通过电振动台施加随机激励,并布置196个测点采集振动信号,采用PolyMAX方法识别模态参数(频率、振型、阻尼比),并通过MAC、MPC指标验证试验有效性(图6~8)。3.模型修正与优化:基于拉丁超立方抽样进行灵敏度分析,并筛选对模态响应影响显著的参数(弹性模量、密度);以遗传算法优化参数,使数值模态与实验模态的频率误差小于5%、MAC值大于0.8(图9~12)。4.动力学模型应用:基于修正后的车体模型建立车辆-轨道刚柔耦合动力学模型,通过模拟正常运行及共振工况下的动态响应,并与现场实测数据对比,验证模型对柔性共振的复现能力(图13~15)。
结论:1.修正后的整备状态车体有限元模型在模态参数模拟上与实验结果高度一致,其频率误差显著降低,MAC指标提升,这表明模型能准确反映车体动态特性;2.基于修正模型的车辆-轨道耦合动力学模型,其动态响应(如加速度时程、功率谱密度)与现场实测数据吻合良好,可有效复现车体柔性共振现象;3.该模型修正方法为高速列车车体柔性振动分析及解决共振问题提供了可靠的数值工具,可进一步用于故障识别和优化设计。

关键词组:高速列车;车体柔性共振;有限元;模型修正;模态频率

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]AkiyamaY, TomiokaT, TakigamiT, et al., 2020. A three-dimensional analytical model and parameter determination method of the elastic vibration of a railway vehicle carbody. Vehicle System Dynamics, 58(4):545-568.

[2]AlkayemNF, CaoMS, ZhangYF, et al., 2018. Structural damage detection using finite element model updating with evolutionary algorithms: a survey. Neural Computing and Applications, 30(2):389-411.

[3]AroraV, 2011. Comparative study of finite element model updating methods. Journal of Vibration and Control, 17(13):2023-2039.

[4]BooSH, KimJH, LeePS, 2018. Towards improving the enhanced Craig–Bampton method. Computers & Structures, 196:63-75.

[5]BragançaC, NetoJ, PintoN, et al., 2022. Calibration and validation of a freight wagon dynamic model in operating conditions based on limited experimental data. Vehicle System Dynamics, 60(9):3024–3050.

[6]CarneTG, DohrmannCR, 1995. A modal test design strategy for model correlation. Proceedings of the 13th International Modal Analysis Conference, p.927-933.

[7]ChangC, DingX, LingL, et al., 2023. Mechanism of high-speed train carbody shaking due to degradation of wheel–rail contact geometry. International Journal of Rail Transportation, 11(3):289-316.

[8]ChenY, JingL, LiT, et al., 2023. Numerical study of wheel–rail adhesion performance of new-concept high-speed trains with aerodynamic wings. Journal of Zhejiang University-SCIENCE A, 24(8):673-691.

[9]GirardiM, PadovaniC, PellegriniD, et al., 2021. A finite element model updating method based on global optimization. Mechanical Systems and Signal Processing, 152:107372.

[10]GongD, DuanY, WangK, et al., 2019. Modelling rubber dynamic stiffness for numerical predictions of the effects of temperature and speed on the vibration of a railway vehicle car body. Journal of Sound and Vibration, 449:121-139.

[11]HeltonJC, DavisFJ, 2003. Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems. Reliability Engineering & System Safety, 81(1):23-69.

[12]HuangCH, ZengJ, 2022. Suppression of the flexible carbody resonance due to bogie instability by using a DVA suspended on the bogie frame. Vehicle System Dynamics, 60(9):3051-3070.

[13]HuYL, GeX, LingL, et al., 2025. Dynamic performance of a high-speed train exiting a tunnel under crosswinds. Journal of Zhejiang University-SCIENCE A, 26(1):21-35.

[14]JiangHW, GaoL, ZhaoWQ, 2021. Model updating of the vehicle–track coupled system based on in-situ dynamic measurements. Construction and Building Materials, 298:123861.

[15]JingL, WangKY, ZhaiWM, 2021. Impact vibration behavior of railway vehicles: a state-of-the-art overview. Acta Mechanica Sinica, 37(8):1193-1221.

[16]JungDS, KimCY, 2013. Finite element model updating on small-scale bridge model using the hybrid genetic algorithm. Structure and Infrastructure Engineering, 9(5):481-495.

[17]KalkerJJ, 1967. On the Rolling Contact of Two Elastic Bodies in the Presence of Dry Friction. PhD Thesis, Delft University, Delft, the Netherlands.

[18]KalkerJJ, 1982. A fast algorithm for the simplified theory of rolling contact. Vehicle System Dynamics, 11(1):1-13.

[19]LiFS, WuH, WuPB, 2021. Vibration fatigue dynamic stress simulation under non-stationary state. Mechanical Systems and Signal Processing, 146:107006.

[20]LiFS, WuH, LiuCT, et al., 2022. Vibration fatigue analysis of high-speed railway vehicle carbody under shaking condition. Vehicle System Dynamics, 60(6):1867-1887.

[21]MalveiroJ, SousaC, RibeiroD, et al., 2018. Impact of track irregularities and damping on the fatigue damage of a railway bridge deck slab. Structure and Infrastructure Engineering, 14(9):1257-1268.

[22]MolodovaM, LiZL, NúñezA, et al., 2014. Validation of a finite element model for axle box acceleration at squats in the high frequency range. Computers & Structures, 141:84-93.

[23]MontenegroPA, NevesSGM, CalçadaR, et al., 2015. Wheel–rail contact formulation for analyzing the lateral train-structure dynamic interaction. Computers & Structures, 152:200-214.

[24]OrlowitzE, BrandtA, 2017. Comparison of experimental and operational modal analysis on a laboratory test plate. Measurement, 102:121-130.

[25]PaigeCC, 1972. Computational variants of the Lanczos method for the eigenproblem. IMA Journal of Applied Mathematics, 10(3):373-381.

[26]PaixãoA, FortunatoE, CalçadaR, 2014. Transition zones to railway bridges: track measurements and numerical modelling. Engineering Structures, 80:435-443.

[27]PapadimitriouC, PapadiotiDC, 2013. Component mode synthesis techniques for finite element model updating. Computers & Structures, 126:15-28.

[28]PedramM, EsfandiariA, KhedmatiMR, 2017. Damage detection by a FE model updating method using power spectral density: numerical and experimental investigation. Journal of Sound and Vibration, 397:51-76.

[29]PeetersB, Van der AuweraerH, GuillaumeP, et al., 2004. The PolyMAX frequency-domain method: a new standard for modal parameter estimation? Shock and Vibration, 11(3-4):395-409.

[30]PiotrowskiJ, KikW, 2008. A simplified model of wheel/rail contact mechanics for non-Hertzian problems and its application in rail vehicle dynamic simulations. Vehicle System Dynamics, 46(1-2):27-48.

[31]PolachO, NicklischD, 2016. Wheel/rail contact geometry parameters in regard to vehicle behaviour and their alteration with wear. Wear, 366-367:200-208.

[32]RamanchaMK, AstrozaR, MadarshahianR, et al., 2022. Bayesian updating and identifiability assessment of nonlinear finite element models. Mechanical Systems and Signal Processing, 167:108517.

[33]ReyndersE, HoubrechtsJ, de RoeckG, 2012. Fully automated (operational) modal analysis. Mechanical Systems and Signal Processing, 29:228-250.

[34]Rezaiee-PajandM, SarmadiH, EntezamiA, 2021. A hybrid sensitivity function and Lanczos bidiagonalization–Tikhonov method for structural model updating: application to a full-scale bridge structure. Applied Mathematical Modelling, 89:860-884.

[35]RibeiroD, CalçadaR, DelgadoR, et al., 2013. Finite-element model calibration of a railway vehicle based on experimental modal parameters. Vehicle System Dynamics, 51(6):821-856.

[36]RibeiroD, CalçadaR, BrehmM, et al., 2021. Calibration of the numerical model of a track section over a railway bridge based on dynamic tests. Structures, 34:4124-4141.

[37]RibeiroD, BragançaC, CostaC, et al., 2022. Calibration of the numerical model of a freight railway vehicle based on experimental modal parameters. Structures, 38:108-122.

[38]SadriM, BrunskogJ, YounesianD, 2016. Application of a Bayesian algorithm for the statistical energy model updating of a railway coach. Applied Acoustics, 112:84-107.

[39]ShiHL, WuPB, 2016. Flexible vibration analysis for car body of high-speed EMU. Journal of Mechanical Science and Technology, 30(1):55-66.

[40]SilvaR, RibeiroD, BragançaC, et al., 2021. Model updating of a freight wagon based on dynamic tests under different loading scenarios. Applied Sciences, 11(22):10691.

[41]SimoenE, de RoeckG, LombaertG, 2015. Dealing with uncertainty in model updating for damage assessment: a review. Mechanical Systems and Signal Processing, 56-57:123-149.

[42]SunJF, ChiMR, JinXS, et al., 2021. Experimental and numerical study on carbody hunting of electric locomotive induced by low wheel–rail contact conicity. Vehicle System Dynamics, 59(2):203-223.

[43]SunY, ShiFF, ZhangS, et al., 2023. Improving the robustness of non-Hertzian wheel–rail contact model for railway vehicle dynamics simulation. Multibody System Dynamics, 59(2):193-237.

[44]SzafrańskiM, 2021. A dynamic vehicle–bridge model based on the modal identification results of an existing EN57 train and bridge spans with non-ballasted tracks. Mechanical Systems and Signal Processing, 146:107039.

[45]Ticona MeloLR, RibeiroD, CalçadaR, et al., 2020. Validation of a vertical train–track–bridge dynamic interaction model based on limited experimental data. Structure and Infrastructure Engineering, 16(1):181-201.

[46]Tran-NgocH, KhatirS, Le-XuanT, et al., 2022. Finite element model updating of a multispan bridge with a hybrid metaheuristic search algorithm using experimental data from wireless triaxial sensors. Engineering with Computers, 38(S3):1865-1883.

[47]UIC (Union Internationale des Chemins de Fer), 1994. Guidelines for Evaluating Passenger Comfort in Relation to Vibration in Railway Vehicles, UIC 513. National Standards of France, Paris, France.

[48]WeiL, ZengJ, ChiMR, et al., 2017. Carbody elastic vibrations of high-speed vehicles caused by bogie hunting instability. Vehicle System Dynamics, 55(9):1321-1342.

[49]XiongCB, LianSD, 2021. Structural damage identification based on improved fruit fly optimization algorithm. KSCE Journal of Civil Engineering, 25(3):985-1007.

[50]YouTW, GongD, ZhouJS, et al., 2022. Frequency response function-based model updating of flexible vehicle body using experiment modal parameter. Vehicle System Dynamics, 60(11):3930-3954.

[51]ZhaiWM, 2019. Vehicle–Track Coupled Dynamics: Theory and Applications. Springer, Singapore.

[52]ZhangXY, JinXL, QiWG, et al., 2008. Vehicle crash accident reconstruction based on the analysis 3D deformation of the auto-body. Advances in Engineering Software, 39(6):459-465.

[53]ZhuHP, LiJJ, TianW, et al., 2021. An enhanced substructure-based response sensitivity method for finite element model updating of large-scale structures. Mechanical Systems and Signal Processing, 154:107359.

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