YU Wennian,DAN Jiaguo,CHEN Kai,et al. Research on vibration response optimization of the urban rail vehicle traction gear transmission system based on combined surrogate model[J]. Journal of Mechanical Transmission,2026,50(3):70-79.
YU Wennian,DAN Jiaguo,CHEN Kai,et al. Research on vibration response optimization of the urban rail vehicle traction gear transmission system based on combined surrogate model[J]. Journal of Mechanical Transmission,2026,50(3):70-79.DOI: 10.16578/j.issn.1004.2539.2026.03.009.
Research on vibration response optimization of the urban rail vehicle traction gear transmission system based on combined surrogate model
Aiming at the excessive vibration of the traction gear transmission system of urban rail vehicles and the problems of long operation time and slow convergence speed in optimization design
a multi-objective optimization method based on a combined surrogate model was proposed to achieve precise improvement of system vibration characteristics and enhancement of optimization efficiency.
Methods
2
Firstly
a lumped parameter method was used to establish the electromechanical coupling dynamic model of the system
and vibration response data were obtained to provide a foundation for subsequent optimization. Secondly
with structural parameters as inputs and vibration responses as outputs
a combined surrogate model integrating Kriging
radial basis function method (RBF) and polynomial response surface was constructed to quickly map the relation between parameters and vibration. Finally
taking bearing support stiffness and damping as optimization variables
the Pareto solution set was solved based on the non-dominated sorting genetic algorithm Ⅱ (NSGA-Ⅱ) to minimize vibration acceleration.
Results
2
After optimization
the root mean square value of the system’s vibration acceleration is reduced by an average of 24%
with the root mean square value of the vertical vibration acceleration of the large gear decreasing by 38.4%; the optimization efficiency is increased by 97%
and the calculation time is shortened from 16 days to 10 min. The vibration suppression effect was stable at different rotational speeds
and the gear bearing capacity is not affected
providing a reference for the optimal design of the traction transmission system of urban rail vehicles.
FAN Naize , LI Bowen , XU Dawei , et al . Strength analysis of gearbox for urban rail train based on Abaqus [J]. Journal of Mechanical Transmission , 2020 , 44 ( 4 ): 120 - 124 .
LIU Guangyu , GONG Dao , ZHOU Jinsong , et al . Global sensitivity analysis and optimization of abnormal elastic vibration of EMU car body based on Sobol’ method [J]. Journal of Central South University (Science and Technology) , 2024 , 55 ( 5 ): 1940 - 1952 .
CHEN Zaigang , LIU Yuqing , ZHOU Ziwei , et al . Summary of dynamics research on traction power transmission system of rail transits [J]. Journal of Traffic and Transportation Engineering , 2021 , 21 ( 6 ): 31 - 49 .
HUANG Guanhua , ZHANG Weihua , FU Yongpei , et al . Stability analysis of parametric vibration for gear transmission system in high-speed train [J]. Journal of Southwest Jiaotong University , 2014 , 49 ( 6 ): 1010 - 1015 .
ZHANG H Y , LI S , ZHANG X . Dynamics model and vibrational response analysis of helical gear-rotor-bearing transmission system [J]. Journal of Vibroengineering , 2024 , 26 ( 2 ): 240 - 263 .
WANG Wenjing , YAN Ruiguo , LI Guangquan , et al . Dynamic characteristics of Chinese standard EMU gearbox housing [J]. Journal of Vibration Engineering , 2019 , 32 ( 3 ): 534 - 539 .
XIAO Qian , YANG Liting , LI Chao , et al . Optimization and design of elastic suspension device for urban rail train [J]. Modern Manufacturing Engineering , 2021 ( 5 ): 64 - 69 .
XU Haibin , SONG Yongzeng , LI Runhua , et al . Optimization of suspension parameters for inner axlebox type single-axle bogie based on Isight [J]. Railway Locomotive & Car , 2015 , 35 ( 3 ): 21 - 24 .
TONG Linjun , ZENG Wei , LIN Xiaojuan , et al . Noise optimization of transmission based on improved combined Kriging model [J]. Journal of Mechanical & Electrical Engineering , 2022 , 39 ( 12 ): 1701 - 1707 .
YU W , MECHEFSKE C K . A new model for the single mesh stiffness calculation of helical gears using the slicing principle [J]. Iranian Journal of Science and Technology,Transactions of Mechanical Engineering , 2019 , 43 ( Suppl.1 ): 503 - 515 .
TIAN De , HU Yue , TAO Lizhuang . Analysis and optimization design of support stiffness of floating components of wind turbine gearbox [J]. Acta Energiae Solaris Sinica , 2023 , 44 ( 4 ): 195 - 202 .
XU Gufu , PENG Xinping , ZHANG Bo , et al . Multi-objective optimization of suspension parameters for rapid passenger locomotive under worn wheel condition [J]. Electric Locomotives & Mass Transit Vehicles , 2024 , 47 ( 5 ): 1 - 8 .
YANG Q C , ZHANG F K , WANG C . Deterministic learning-based neural PID control for nonlinear robotic systems [J]. IEEE/CAA Journal of Automatica Sinica , 2024 , 11 ( 5 ): 1227 - 1238 .
LI Yonghua , WEI Wusong , ZHANG Xu . Optimization of gear modification amount based on polynomial response surface proxy model [J]. Journal of Mechanical Transmission , 2020 , 44 ( 11 ): 27 - 33 .
SONG X G , LV L Y , LI J L , et al . An advanced and robust ensemble surrogate model:extended adaptive hybrid functions [J]. Journal of Mechanical Design , 2018 , 140 ( 4 ): 041402 .
YUAN Z X , LIANG P , SILVA T , et al . Parameter selection for model updating with global sensitivity analysis [J]. Mechanical Systems and Signal Processing , 2019 , 115 : 483 - 496 .
WANG Xiaoguang , DANG Litao , MA Ming . A robust estimation method for response surface model updating based on vibration frequency [J]. Journal of Highway and Transportation Research and Development , 2022 , 39 ( 2 ): 77 - 84 .
WANG Y T , PANG Y , XUE T H , et al . Ensemble learning based hierarchical surrogate model for multi-fidelity information fusion [J]. Advanced Engineering Informatics , 2024 , 60 : 102535 .
HE Yanru , SONG Baowei , CAO Yonghui . Mixture surrogate model based structural optimization design of multiple intersecting spheres for automatic undersea vehicle [J]. Journal of Unmanned Undersea Systems , 2017 , 25 ( 6 ): 410 - 417 .
DEB K , PRATAP A , AGARWAL S , et al . A fast and elitist multiobjective genetic algorithm:NSGA-Ⅱ [J]. IEEE Transactions on Evolutionary Computation , 2002 , 6 ( 2 ): 182 - 197 .