An intelligent control approach for heavy haul trains using deep reinforcement learning

Author(s):  
Wentao Liu ◽  
Shuai Su ◽  
Tao Tang
2020 ◽  
Vol 2 (2) ◽  
pp. 133-147
Author(s):  
Chun Tian ◽  
Mengling Wu ◽  
Lu Zhu ◽  
Jun Qian

Abstract An intelligent control method is proposed for the electronically controlled pneumatic (ECP) braking system of a heavy-haul train. The gradient of the ramp is estimated using a Kalman filter in real time and the braking force is adjusted by the backstepping method, so that vehicles on different gradients change their brake pressure with the change in the gradient to keep the instantaneous deceleration of each vehicle consistent, thus reducing the longitudinal impact between vehicles. The longitudinal impact of heavy-haul trains with and without intelligent control under different gradients, initial braking speeds, loads and complex terrains are simulated and analysed. The results show that when the intelligent control is applied, each vehicle can adjust its brake pressure in time according to the change of gradient. The intelligent control method can effectively alleviate the longitudinal impact of vehicles, and the reduction rate remains greater than 40% under the influence of various factors.


2021 ◽  
Author(s):  
Jiangtao Zhou ◽  
Hua Zheng ◽  
Dongzhu Zhao ◽  
Yingxue Chen

2018 ◽  
Vol 18 (03) ◽  
pp. 1850035 ◽  
Author(s):  
Zhihui Zhu ◽  
Lidong Wang ◽  
Zhiwu Yu ◽  
Wei Gong ◽  
Yu Bai

This paper presents a non-stationary random vibration analysis of railway bridges under moving heavy-haul trains by the pseudo-excitation method (PEM) considering the train-track-bridge coupling dynamics. The train and the ballasted track-bridge are modeled by the multibody dynamics and finite element (FE) method, respectively. Based on the linearized wheel-rail interaction model, the equations of motion of the train-ballasted track-bridge coupling system are then derived. Meanwhile, the excitations between the rails and wheels caused by the random track irregularity are transformed into a series of deterministic pseudo-harmonic excitation vectors by the PEM. Then, the random vibration responses of the coupling system are obtained using a step-by-step integration method and the maximum responses are estimated using the 3[Formula: see text] rule for the Gaussian stochastic process. The proposed method is validated by the field measurement data collected from a simply-supported girder bridge (SSB) for heavy-haul trains in China. Finally, the effects of train speed, grade of track irregularity, and train type on the random dynamic behavior of six girder bridges for heavy-haul railways are investigated. The results show that the vertical acceleration and dynamic amplification factor (DAF) of the midspan of the SSB girders are influenced significantly by the train speed and track irregularity. With the increase in the vehicle axle-load, the vertical deflection-to-span ratio ([Formula: see text]) of the girders increases approximately linearly, but the DAF and vertical acceleration fail to show clear trend.


2020 ◽  
Author(s):  
Lars Brinkschulte ◽  
◽  
Marina Graf ◽  
Marcus Geimer ◽  
◽  
...  

Author(s):  
Hongwei Wang ◽  
Qianqian Zhao ◽  
Siyu Lin ◽  
DongLiang Cui ◽  
Chengcheng Luo ◽  
...  

Author(s):  
Auteliano A. Santos ◽  
Matheus V. Lopes ◽  
Vanessa Gonçalves ◽  
Jony J. Eckert ◽  
Thiago S. Martins

Long heavy-haul trains are now a reality, especially for ore transportation. In some railways, compositions of up to 330 wagons are in service, requiring several locomotives. Trains like that travel long distances, sometimes through cities or in uninhabited regions. They are driven by just one driver which must keep the whole train working safely on the track. The wagons don’t have any source of electrical energy to power sensors and to transmit their signals to the locomotive; nor wireless communication. In fact, in some of these railways, there is no internet along with the track out of the cities. One important indicator of the safety of the train is the force between the wagons during the trip, through the shunting. Using strain gauges to measure these forces is a possible solution and ultrasonic stress sensors (UST) is a suitable alternative. UST with Lcr waves requires a low amount of energy and can be employed in rusty and dirty places. However, they also need an energy source. Wind and solar solutions are not always adequate because, unfortunately, there are places where these components have economic value and they can be stolen. A possible source of energy to power the USTs could be the Vibration Energy Harvester (VEH). These simple and not expensive systems can be built in small packs, giving the energy to measure the forces and transmit the data to the locomotive or designated sites along the track. This work aims to evaluate the possibility of using VEH to power USTs to measure the forces between the wagons during the journey. Knowing that the oscillation in the shunting has a very low frequency, the work intent to optimize a multi-beam VEH to be able to capture the highest amount of energy possible, in a very small arrangement, using genetic algorithm. The result shows that VEH is an adequate alternative to power autonomous UST sensors.


2020 ◽  
pp. 002029402095245 ◽  
Author(s):  
Jing He ◽  
Xingxing Yang ◽  
Changfan Zhang ◽  
Jianhua Liu ◽  
Qian Zhang ◽  
...  

To address the tracking control problem of heavy-haul trains (HHTs) with input saturation during operation, an anti-saturation sliding mode (SMES) control method based on dynamic auxiliary compensator (DAC) is presented. Firstly, an HHT model with nonlinear coupling and uncertain disturbances is built. Secondly, a new type of DAC is introduced to overcome the difficulty of traditional dynamic auxiliary compensator (TDAC) with a large upper bound on the compensation signal. Finally, an anti-saturation SMES control algorithm is designed to reduce the influence of input saturation on the tracking accuracy of each carriage. Simulation results verify the effectiveness of the algorithm in terms of tracking accuracy, anti-interference, and anti-saturation.


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