Multi-parameter joint optimization for double-strip high-speed pantographs to improve pantograph-catenary interaction quality

Wu, Mengzhen; Xu, Xianghong; Yan, Yubin; Luo, Yi; Huang, Sijun; Wang, Jianshan

doi:10.1007/s10409-021-09018-x

Cited by 4 publications

(6 citation statements)

References 22 publications

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“…The FEM calculated values of the above pantograph-catenary finite element model (Figure 1) have been verified using the measured data from line tests on the Datong-Xi'an High-speed Railway Line [7] and the trade standard EN50318:2018 [22,23]. The computational cost of the pantographcatenary finite element model was about 10 core hours when calculating a single pantograph-catenary interaction case.…”

Section: Pantograph-catenary Finite Element Model [7]mentioning

confidence: 64%

“…The catenary parameters of the stitched catenary of Datong-Xi'an High-speed Railway Line [7] were adopted and set k 1 = 74 N/m, c 3 = 50 N•s/m, and c 2 = 10 N•s/m. Each decision variable in X used the same value range as in our team's previous article [21].…”

Section: Performance Evaluation Of Prediction Modelmentioning

confidence: 99%

“…The nonlinear spring elements, which only bear tension, are often used to simulate the droppers. The spring-lumped mass systems are used to simulate the steady arms, and the lumped masses are used to simulate various clamps [2,[5][6][7].…”

Section: Introductionmentioning

confidence: 99%

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Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

Wu,

Xu,

Zhang

et al. 2024

Applied Sciences

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As a traditional numerical simulation method for pantograph–catenary interaction research, the pantograph–catenary finite element model cannot be applied to the real-time monitoring of pantograph–catenary contact force, and the computational cost required for the multi-parameter joint optimization of the pantograph–catenary system with the finite element model is very high. In this paper, based on the selective crow search algorithm–radial basis function (SCSA-RBF) network, the time-domain signal of the panhead acceleration, which can be obtained in real-time through non-contact test technology, is taken as the boundary condition to directly solve the pantograph dynamic equation and a data-physics coupling model that can quickly predict the pantograph–catenary interaction is proposed. The prediction model is trained and verified using the dataset generated through the finite element model. Furthermore, the prediction model is applied to the multi-parameter joint optimization of six pantograph dynamic parameters and nine pantograph dynamic parameters, considering nonlinear panhead stiffness, and optimization suggestions under various speeds and filtering frequencies are given.

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Section: Pantograph-catenary Finite Element Model [7]mentioning

confidence: 64%

Section: Performance Evaluation Of Prediction Modelmentioning

confidence: 99%

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Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

Wu,

Xu,

Zhang

et al. 2024

Applied Sciences

Self Cite

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“…The steps for data set design are as follows: First, draw 12,000 samples by using the Latin hypercube sampling method [20]. Secondly, the time domain curves of contact force for the above 12,000 samples were obtained using the pantograph-catenary finite element method [21], and the lifting force exerted on m 1 was adjusted during calculation to ensure the deviation between the average contact force and the upper limit [6] was lower than 0.5 N. Based on those time domain curves after low-pass filtering at 20 Hz or 40 Hz, the theoretical values of the SDCF could be calculated, and databases of the SDCFs at the two low-pass filtering frequencies were constructed. Finally, the training set and the validation set were divided from the data set based on the hold-out method, and the test set was composed of the remaining examples.…”

Section: Design Of Data Setsmentioning

confidence: 99%

Contact Force Surrogate Model and Its Application in Pantograph–Catenary Parameter Optimization

Zhou,

2024

Applied Sciences

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The significant increase in the speed of high-speed trains has made the optimization of pantograph–catenary parameters aimed at improving current collection quality become one of the key issues that urgently need to be addressed. In this paper, a method and solutions are proposed for optimizing multiple pantograph–catenary parameters, taking into account the speed levels and engineering feasibility, for pantograph–catenary systems that contain dozens of parameters and exhibit strong nonlinear coupling characteristics. Firstly, a surrogate model capable of accurately predicting the standard deviation of contact force based on speed and 14 pantograph–catenary parameters was constructed by using the pantograph–catenary finite element model and feedforward neural network. Secondly, sensitivity analysis and rating of the pantograph–catenary parameters under different speeds were conducted using the variance-based method and the surrogate model. Finally, by combining the sensitivity analysis results and the Selective Crow Search Algorithm, joint optimization of 10 combinations of the pantograph–catenary parameters across the entire speed range was performed, providing efficient pantograph–catenary parameter optimization solutions for various engineering conditions.

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“…The relationship between dynamic contact resistance and these three conditions [1] has been clarified by establishing the corresponding mathematical model [2] . The experimental results show that increasing the contact pressure, reducing the sliding speed and contact current can appropriately reduce the contact resistance and improve the pantograph-catenary current collection quality [3] . In addition, some scholars have obtained the best normal load of pantograph during actual operations by comprehensively considering the current collecting efficiency, current collection stability and wear rate of sliding plate [4] .…”

Section: ⅰ Introductionmentioning

confidence: 97%

Impact of Surface Roughness on Pantograph-Catenary Current Collection Quality

et al. 2022

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In the pantograph-catenary system, the change of the surface roughness of pantograph sliding plate directly affects the current collection quality of electric locomotive. In this paper, a large number of current-carrying friction experiments have been carried out on the self-developed high-performance sliding electric contact experimental machine, and the effects of the surface roughness of the sliding friction pair on important performance parameters have been studied, including pantograph-catenary contact resistance (Rj), current carrying efficiency (η), current collection stability (δ) and the friction coefficient (µ). Further, the current conduction mechanism is revealed by the microscopic approach. In order to quantitatively reveal the effect of roughness on each evaluation index of current collecting performance, the paper formulates the functional relationship between Ra (arithmetic mean height of contour) and Rj, η, δ, µ by nonlinear fitting. On this basis, a comprehensive evaluation equation is established by the entropy weight method, and then the optimal Ra value is derived for the best pantograph-catenary current collecting performance. The experimental results show that with the increase of the surface roughness Ra of the sliding plate, Rj decreases first and then increases, while η increases first and then decreases, δ increases monotonically, and µ gradually increases. The optimal pantograph-catenary current collection condition can be achieved by reconciliation of these indices. The research results of this paper provide a theoretical basis for improving the current collection quality of pantograph-catenary systems, and is useful for material selection or new type design of pantograph sliding plates.

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Multi-parameter joint optimization for double-strip high-speed pantographs to improve pantograph-catenary interaction quality

Cited by 4 publications

References 22 publications

Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

Pantograph–Catenary Interaction Prediction Model Based on SCSA-RBF Network

Contact Force Surrogate Model and Its Application in Pantograph–Catenary Parameter Optimization

Impact of Surface Roughness on Pantograph-Catenary Current Collection Quality

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