Optimal allocation method of electric/air braking force of high-speed train considering axle load transfer

Abstract

Reasonable distribution of braking force is a factor for a smooth, safe, and comfortable braking of trains. A dynamic optimal allocation strategy of electric-air braking force is proposed in this paper to solve the problem of the lack of consideration of adhesion difference of train wheelsets in the existing high-speed train electric-air braking force optimal allocation strategies. In this method, the braking strategy gives priority to the use of electric braking force. The force model of a single train in the braking process is analyzed to calculate the change of adhesion between the wheel and rail of each wheelset after axle load transfer, and then the adhesion of the train is estimated in real time. Next, with the goal of maximizing the total adhesion utilization ratio of trailer/motor vehicles, a linear programming distribution function is constructed. The proportional coefficient of adhesion utilization ratio of each train and the application upper limit of braking force in the function is updated according to the change time point of wheelset adhesion. Finally, the braking force is dynamically allocated. The simulation results of Matlab/Simulink show that the proposed algorithm not only uses the different adhesion limits of each trailer to reduce the total amount of braking force undertaken by the motor vehicle, but also considers the adhesion difference of each wheelset. The strategy can effectively reduce the risk and time of motor vehicles during the braking process and improve the stability of the train braking.

Keywords

Braking force allocation / Wheelset / Dynamicity / Axle load transfer total / Adhesion utilization ratio

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant Nos. 62173137, 52172403, 62303178).

References

[1] C. Wang, J. Liu. An efficient anomaly detection for high-speed train braking system using broad learning system. IEEE Access, 9 (2021), pp. 63825-63832.

[2] M. Zhang, R. Hu, J. Mo, et al., A cross-domain state monitoring method for high-speed train brake pads based on data generation under small sample condition. Measurement, 226 (2024) 114074.

[3] P. Surachon, T. Ratniyomchai, T. Kulworawanichpong, Aerodynamic brake study of reducing braking distance and decreasing using the energy of braking of high-speed trains, In: 2020 International Conference on Power, Energy, and Innovations (ICPEI), Chiangmai, (2020) 21–24.

[4] S. Hajiaghasi, Z. Rafiee, A. Salemnia, et al., New control strategy for optimum use of regenerative braking energy in electric train based on energy storage systems, In: 2019 Iranian Conference on Renewable Energy & Distributed Generation (ICREDG), Tehran, (2019) 1–5.

[5] K. Teramoto, K. Ohishi, S. Makishima, et al., Cooperative control of regenerative brake and mechanical brake for a two-coach train, In: IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society, Montreal, (2012) 1707–1712.

[6] S. Zhang, Y. Lin, L. Zhao, et al., Research on electric control brake system based on railway vehicle. J. Phys.: Conf. Ser., 2417 (2022) 012035.

[7] V.M. Konstantinova, V.I. Varavin, R.R. Dagaev. Application of regenerative braking on electric rolling stock. J. Phys.: Conf. Ser., 2176 (2022) 012026.

[8] X.R. Wang. Optimization of electro-pneumatic braking distribution for high-speed train, Dissertation for Master’s Degree. Beijing Jiaotong University, Beijing (2016).

[9] S.J. Wen, D.G. Shun. Research on air braking force distribution mode of urban rail train. Roll. Stock, 53(8)(2015), pp. 9-12.

[10] J.F. Qin. Study on the braking force redistribution of high-speed train in the slip, Dissertation for Master’s Degree. Beijing Jiaotong University, Beijing (2013).

[11] C. Yang, J. Lin, L. Tian, et al., Numerical study of wheel-rail adhesion performance of new-concept high-speed trains with aerodynamic wings. J. Zhejiang Univ. -Sci. A, 24(8)(2023), pp. 673-691.

[12] S. Lin, X. Fang, Z. Li, et al., Adhesion control strategy for trains with driven independently rotating wheels considering active guidance. IET Elec. Power Appl., 17(10)(2023), pp. 1321-1333.

[13] J. He, L. Shi, C. Zhang, et al., Research on electro-pneumatic braking force optimization distribution for electric multiple units, Comput. Eng., 44(10)(2018), pp. 314-320.

[14] P. Chen, S. Gao, Q. Meng. Braking force distribution strategy of EMU. Railw. Locomot. Car, 38(4)(2018), pp. 24-29.

[15] S. Gao, J. Qin, C. Wen, et al., Research on braking force distribution in axle controlled braking control system based on axle load transfer. Locomot. Roll. Stock Technol., 3 (2023), pp. 1-4.

[16] Y.-Z. Jin. Braking modeling and parameter identification for high-speed train, Dissertation for Master’s Degree. Xi’an University of Technology, Xi’an (2019).

[17] G. Xie, Y.-Z. Jin, X.-H. Hei, et al., Adaptive identification of time-varying environmental parameters in train dynamics model, Acta Automat. Sin., 45(12)(2019), pp. 2268-2280.

[18] J.-S. Shao. The research and analysis of high-speed EMU braking system, Dissertation for Master’s Degree. Southwest Jiaotong University, Chendu (2015).

[19] G. Xie, D. Zhang, X.-H. Hei, et al., Online identification method of time-varying parameters for longitudinal dynamics model of high-speed train. J. Traffic Trans. Eng., 17(1)(2017), pp. 71-81.