Study on Simulation Method of Pantograph-Catenary System Considering Ice Coating

Conference paper
Part of the Lecture Notes in Mechanical Engineering book series (LNME)


The icing problem of catenary is becoming more and more prominent with the expansion of the distribution range of rail transit lines. Ice coating on catenary will affect the sliding of pantograph and the power supply quality of train. In serious cases, the phenomenon of arc tension between catenary and pantograph will also occur, which threatens the normal operation of trains. The equivalent density method and the uniform load method of icing are studied to analyze the icing problem of pantograph-catenary system. The similarities and differences between the two simulation methods are compared. The pantograph-catenary dynamics simulation analysis is carried out based on the multi-rigid body model of pantograph. The results show that the icing of catenary will affect the current collecting quality of pantograph-catenary system. The difference between the two models in calculating the dynamic response of pantograph-catenary system after icing becomes obvious with the increase of icing thickness, and the mechanism of the difference is analyzed.


Pantograph-catenary current collection Ice coating Equivalent density Uniform load 


  1. 1.
    Hou, J., Li, Y., Sun, Z.: Unbalanced tensions and vertical space calculation of transmission lines under non-uniform ice-coating and ice-shedding. Energy Procedia 17, 1034–1042 (2012)CrossRefGoogle Scholar
  2. 2.
    Jamaleddine, A., McClure, G., Rousselet, J., et al.: Simulation of ice-shedding on electrical transmission lines using ADINA. Comput. Struct. 47(4–5), 523–536 (1993)CrossRefGoogle Scholar
  3. 3.
    Xie, J.J., Wang, Y., Liu, Z.M., et al.: Finite element simulation and small scale model experiment of catenary icing. Proc. CSEE 33, 185–192 (2013)Google Scholar
  4. 4.
    Duan, F., Liu, Z., Song, Y., et al.: Influences of ice load and air damping on dynamic current collection of pantograph-iced catenary. J. Southwest Jiaotong Univ. (1), 25 (2016)Google Scholar
  5. 5.
    Colominas, M.A., Schlotthauer, G., Torres, M.E.: Improved complete ensemble EMD: a suitable tool for biomedical signal processing. Biomed. Signal Process. Control 14, 19–29 (2014)CrossRefGoogle Scholar
  6. 6.
    Xue, X., Zhou, J., Xu, Y., et al.: An adaptively fast ensemble empirical mode decomposition method and its applications to rolling element bearing fault diagnosis. Mech. Syst. Signal Process. 62, 444–459 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.State Key Laboratory of Traction PowerSouthwest Jiaotong UniversityChengduChina

Personalised recommendations