Adhesion Control of High Speed Train Based on Vehicle-control System

Wang, Song; Wang, Xiongguo; Huang, Jingchun; Sun, Pengfei; Wang, Hongtao

doi:10.1109/iciea51954.2021.9516096

Cited by 2 publications

(1 citation statement)

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“…They also proposed an adaptive control method that effectively controls the adhesion utilization rate of the traction system. Song Wang et al [13] proposed an adhesion control method based on optimal torque search for high-speed trains, which can achieve stable operation of trains in the optimal adhesion state under changes of track surface and high-speed driving conditions, effectively reducing the idle rate of the wheel and improving train adhesion utilization. Shuai Zhang et al [14] proposed a sliding mode control method, which used recursive least squares method based on enhanced forgetting factor to solve the problem of wheel anti lock on heavy-duty trains.…”

Section: Introductionmentioning

confidence: 99%

Reinforcement Learning Based Speed Control with Creep Rate Constraints for Autonomous Driving of Mining Electric Locomotives

Li,

Zhu,

2024

Applied Sciences

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The working environment of mining electric locomotives is wet and muddy coal mine roadway. Due to low friction between the wheel and rail and insufficient utilization of creep rate, there may be idling or slipping between the wheels and rails of mining electric locomotives. Therefore, it is necessary to control the creep rate within a reasonable range. In this paper, the autonomous control algorithm for mining electric locomotives based on improved ε-greedy is theoretically proven to be convergent and effective firstly. Secondly, after analyzing the contact state between the wheel and rail under wet and slippery road conditions, it is concluded that the value of creep rate is an important factor affecting the autonomous driving of mining electric locomotives. Therefore, the autonomous control method for mining electric locomotives based on creep control is proposed in this paper. Finally, the effectiveness of the proposed method is verified through simulation. The problem of wheel slipping and idling caused by insufficient friction of mining electric locomotives in coal mining environments is effectively suppressed. Autonomous operation of vehicles with optimal driving efficiency can be achieved through quantitative control and utilization of the creep rate between wheels and rails.

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Section: Introductionmentioning

confidence: 99%