vehicle system dynamics
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2019 ◽  
Vol 58 (1) ◽  
pp. 74-91 ◽  
Author(s):  
Yongzhi Jiang ◽  
Pingbo Wu ◽  
Jing Zeng ◽  
Yingsheng Zhang ◽  
Yunchang Zhang ◽  
...  

2018 ◽  
Vol 16 (2) ◽  
pp. 126-138 ◽  
Author(s):  
Chris Bosomworth ◽  
Maksym Spiryagin ◽  
Sanath Alahakoon ◽  
Colin Cole

Author(s):  
Qing Wu ◽  
Maksym Spiryagin ◽  
Colin Cole

Simulations of three-dimensional train system dynamics for long freight railway trains with consideration being given to all degrees-of-freedom of all essential components of all vehicles have not been reported due to the challenge of long computing time. This paper developed a parallel computing scheme for three-dimensional train system dynamics. Key modeling techniques were discussed, which include modeling of longitudinal train dynamics, single vehicle system dynamics and multibody coupler systems. Assume that there are n vehicles in the train, then, n + 2 cores are needed. The first core (core 0) is used as the master core; the last core (core n + 1) is used for air brake simulation; the rest of the cores (core 1 to core n) are used for the computing of single vehicle system dynamics for all n vehicles in parallel. During the simulation, the master core collects the results from core n + 1 and then sends the air brake pressures and knuckle forces to core 1 to core n. core 1 to core n execute vehicle system dynamics simulations and then send the coupler kinematics to the master core. The details of the parallel computing scheme were presented in this paper. The feasibility of the computing scheme has been demonstrated by a simulation of a long heavy haul train that has 214 vehicles. A 3 h train trip was simulated; 216 cores were used. The accumulated computing time of all cores was about 253 days, while the wall-clock time was about 29 h. Such computing speed has made the simulations of three-dimensional train system dynamics practical.


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