Data-driven design of brake pad composites for high-speed trains

Lingzhi Wu; Peng Zhang; Bin Xu; Jie Liu; Haiqing Yin; Lin Zhang; Xue Jiang; Cong Zhang; Ruijie Zhang; Yongwei Wang; Xuanhui Qu

Journal of Materials Research and Technology (Nov 2023)

Data-driven design of brake pad composites for high-speed trains

Lingzhi Wu,
Peng Zhang,
Bin Xu,
Jie Liu,
Haiqing Yin,
Lin Zhang,
Xue Jiang,
Cong Zhang,
Ruijie Zhang,
Yongwei Wang,
Xuanhui Qu

Affiliations

Lingzhi Wu: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Peng Zhang: Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
Bin Xu: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Jie Liu: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Haiqing Yin: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China; Corresponding author. Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083 China.
Lin Zhang: Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
Xue Jiang: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China; School of Mechanical Engineering, Chongqing Three Gorges University, Chongqing 404000, China
Cong Zhang: Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Ruijie Zhang: Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Yongwei Wang: Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China
Xuanhui Qu: Beijing Advanced Innovation Center for Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China; Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China; Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China; School of Mechanical Engineering, Chongqing Three Gorges University, Chongqing 404000, China; Corresponding author. Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China.

Journal volume & issue: Vol. 27
pp. 1058 – 1071

Abstract

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Brake pads play a vital role in controlling the operation of high-speed trains with over 300 km/h. Currently the copper-based composites produced by powder metallurgy techniques have been proved as one of the ideal materials. However，the braking performance is strongly influenced by the chemical composition, production, microstructure as well as the working conditions. The intrinsic mechanism of the thermal fade and wear loss under thermal and mechanical coupled influence has not yet been fully revealed. As of late, machine learning algorithms have attracted widespread attention and extraordinary results has been accomplished in materials science and engineering. In this study the algorithms for predicting the braking performance of copper-based brake pads are developed. A new PM copper-based alloy, was designed via the models of the coefficient of friction (COF) and wear loss. The braking test results of this alloy show that the average COF was 0.37 at stable stage I and thermal recession decrease only 0.012 at stage II when under 350 km/h/0.48 MPa continuous braking for 10 times. And the total wear loss is only 1.30 g when under braking from 200 km/h to 350 km/h with pressure from 0.31 MPa to 0.48 MPa. Compared with the commercial brake pads, our designed alloy exhibits excellent braking performance with COF for thermal fade reduced to 21% and the total wear loss reduced to 20%.

Published in Journal of Materials Research and Technology

ISSN: 2238-7854 (Print); 2214-0697 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Technology: Mining engineering. Metallurgy
Website: https://www.journals.elsevier.com/journal-of-materials-research-and-technology/

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