The interaction performance of the pantograph-catenary is of great importance as it directly determines the current collection quality and operational safety of trains. The finite element method (FEM) is dominantly used for simulating pantograph-catenary interaction, which is normally computationally heavy. In this work, addressing the tremendous computational cost of FEM models, a surrogate model for fast simulations of pantograph-catenary interaction is proposed using deep learning. A dataset containing 30,000 cases of pantograph-catenary interaction is generated by a validated FEM model. A Long-Short-Term-Memory (LSTM) neural network is proposed to learn the inherent nonlinearity between the input model parameters and the output pantograph-catenary contact force from data. The resulting prediction performance indicates that contact forces predicted by the surrogate model are consistent with those simulated by FEM, while the computational efforts of the surrogate model are negligible compared with FEM. Prediction performances using different network architectures and configurations are compared to determine the optimal setting for a pantograph-catenary system. The LSTM-based surrogate model shows high efficiency for simulating pantograph-catenary interactions and promising practicability in optimising catenary structural parameters for design or upgrade.

In railway pantograph-catenary systems, the contact surfaces undergo wear in long-term operations, directly affecting interaction performance and potentially deteriorating the current collection quality. The effect of contact wire wear (CWW) on the current collection quality should be evaluated to understand the system's health status in operations. This article presents a stochastic analysis of the pantograph-catenary interaction performance with different levels of CWW based on four years of measurement data. The power spectral density (PSD) estimation is carried out on the measured CWW to obtain their frequency representations. The random time histories of CWW are generated based on the PSDs. A nonlinear finite element model of catenary with a lumped-mass pantograph is built. Using the Monte Carlo method, the stochastic analysis of pantograph-catenary contact force is carried out to investigate the distribution and dispersion of assessment indices with different levels of CWW. The results indicate that the CWW mainly affects the maximum and minimum contact forces instead of the contact force standard deviation. The optimal pantograph-catenary interaction performance is observed certain years after CWW is formed, depending on the traffic density of the railway line, which is at the second year in the presented case study. Then, the performance declines with an increase in service time. Also, higher operating speed causes a more significant dispersion in assessment indices representing a lower current collection quality, particularly at the maximum operating speed (70% of the catenary wave propagation speed).

The wind deflection of overhead contact lines (OCLs) challenges the stable and safe operation of electrified railways. The steady wind causes the static deflection of the contact line, while the fluctuating wind leads to the OCL buffeting. This paper performs a response spectrum analysis of the wind deflection caused by the combined effects of steady and fluctuating winds. Considering the initial configuration of OCL, an absolute nodal coordinate formulation method is employed to model the OCL. A spatial wind field including the fluctuating wind in three directions is constructed and the aerodynamic forces on the OCL are derived. A nonlinear solution procedure is proposed to include the geometrical nonlinearity and dropper slackness in the evaluation of static wind deflection. The pseudo-excitation method is utilised to evaluate the buffeting response of the OCL with stochastic wind load. The analysis results indicate that the dropper slackness has a significant effect on the vertical static deflection. Under an extreme wind speed of 40 m/s, the contact line is always within the safe working range of pantograph head when only the steady wind load is considered. However, the stochastic wind load causes non-negligible fluctuation of OCL, and the contact line may be outside of the pantograph working range under the same wind speed. Sensitivity analyses on the effects of some key parameters to the OCL buffeting suggest that the increases of damping ratio and the tension class are effective measures to improve the wind-resistance capability of OCL.

In this article, a novel fan-out panel-level printed circuit board (PCB)-embedded package for phase-leg silicon carbide (SiC) metal-oxide-semiconductor field-effect transistor (MOSFET) power module is presented. Electro-thermo-mechanical co-design was conducted, and the maximum package parasitic inductance was found to be about 1.24 nH at 100 kHz. Compared with wire-bonded packages, the parasitic inductances of the PCB-embedded package decreased at least by 87.6%. Compared with blind via structure, the thermal resistance of the proposed blind block structure reduced at most by about 26%, and the stress of the SiC MOSFETs decreased by about 45.2%. Then, a novel PCB-embedded packaging process was developed, and three key packaging processes were analyzed. Furthermore, effect of PCB-embedded package on static characterization of SiC MOSFET was analyzed, and it was found that: 1) Output current of PCB-embedded package was decreased under a certain gate-source voltage compared to SiC die; 2) Miller capacitance of SiC MOSFET was increased thanks to parasitic capacitance induced by package; and 3) compared with SiC die, nonflat miller plateau of the PCB-embedded package extends, and as drain-source voltage increases, the nonflat miller plateau extends. Lastly, switching characteristics of the PCB-embedded package and TO-247 package were compared. The results show that the PCB-embedded package has smaller parasitic inductances.

This paper studies the evolvement of the wear irregularity of contact wire using wire thickness data measured yearly from a section of railway catenary. The power spectral density and time–frequency representation based on the wavelet transform are employed for data analysis, with an emphasis on local wear irregularities that are crucial for contact wire condition assessment. To investigate the cause of wear irregularity evolvement and the mutual influence with the pantograph–catenary dynamic interaction, simulations considering the influence of wear irregularity are carried out based on the finite element method. Analyses of the actual wear irregularities and the dynamic contact force under singular and complex wear irregularities are performed. Although the wear irregularity has limited impact on the pantograph–catenary interaction, it can induce the vibration of pantograph and contact wire that will lead to a notable increase of contact force standard deviation. The evolvement of wear irregularity is closely associated with the span length and dropper distribution of catenary structure and the running direction of pantograph. In addition, it is found feasible to detect the wear irregularity based on contact force, on condition that the sampling frequency is high enough to reflect the indicative frequencies.