FULL FLEXIBLE MODEL UPDATING OF SINGLE-STRIP PANTOGRAPH BASED ON MODAL TEST

Since electric multiple units obtain electricity from the catenary through the pantograph, a good pantograph-catenary contact is essential for ensuring current collection quality for the train. With the increase of the running speed of the train, the issue of the pantograph-catenary dynamic characteristics becomes increasingly noticeable. As the traveling speed increases, the elastic modes of the pantograph and the high-frequency interaction between the pantograph and catenary will be excited by high-frequency excitation such as catenary irregularity and aerodynamic effects. The three lumped mass model that only considers the three vertical free degree of the pantograph is no longer suitable for high-frequency pantograph-catenary dynamics analysis. In order to design the dynamic parameters of pantographs at higher speed and evaluate the current collection quality of the pantograph-catenary system, a full flexible model of the pantograph that reflects the structural elastic modes is required. In this paper, an updating method based on the full flexible model of pantographs is proposed. Firstly, a new single-strip high-speed pantograph was tested, and modal characteristics of two vertical coupled vibration modes and six vertical elastic modes within 260 Hz were obtained. Then, an analysis on the sensitivity of the modal frequency of the pantograph to material parameters was conducted. It was found that the elastic modulus and density of the strip, upper arm and lower arm, and the spring stiffness of the pan head, have a significant influence on the eight vertical frequencies of the pantograph, and thus the model parameters to be updated were determined. Finally, by using particle swarm optimization, an updated full flexible model was obtained, which was in good agreement with the experimental results, with a deviation of only 5.2%. In addition, a modal identification method based on modal assurance criterion was proposed, which can achieve automatic modal identification in the process of model updating with 100% accuracy.