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Optimal allocation method of electric/air braking force of high-speed train considering axle load transfer
- Source :
- High-Speed Railway, Vol 2, Iss 2, Pp 77-84 (2024)
- Publication Year :
- 2024
- Publisher :
- KeAi Communications Co., Ltd., 2024.
-
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.
Details
- Language :
- English
- ISSN :
- 29498678
- Volume :
- 2
- Issue :
- 2
- Database :
- Directory of Open Access Journals
- Journal :
- High-Speed Railway
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3f05bca4aeb4fcd8fb62bbdbed6a9ff
- Document Type :
- article
- Full Text :
- https://doi.org/10.1016/j.hspr.2024.04.004