Trajectory Optimization Method of Freight Suspended Monorail Train in Complex Environment
1. School of Automation and Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;
2. Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphic & Image Processing, Lanzhou 730070, China
Online published: 2025-02-26
There are several tens of kilometers of high drop and large sandstorm areas between many mines and main roads in western China. In order to improve the adaptability and intelligence of the freight suspended monorail train in this complex environment, an applicable trajectory optimization method was studied. The dynamic operation process of freight rail was analyzed. Considering the characteristics of large line drop, complex line type, and train deviation from plan due to environmental interference, an improved method for generating long ramp train operation curve was designed with the goal of comprehensive optimization of time and energy consumption. On this basis, the overall adjustment model in the interference scene was established to avoid or reduce the deterioration and propagation of delay in time. Finally, the data of a test line was used for simulation verification. The results show that: Compared with the standard control method, the lower limit of net energy consumption under the improved control method is optimized. In a virtual interval, the traction energy consumption of the improved control method is reduced by 84.13%, the brake recovery is reduced by 43.15%, the net energy consumption difference is 5.20 kW·h, and the net energy consumption difference is 41.82 kW·h in the multi-interval interference scene of the test line. It can solve the trajectory optimization problem of freight suspended monorail train in complex environment, effectively guarantee the redemption rate of transportation plan and reduce operating costs.
LÜ Weixi1, MIN Yongzhi1, 2, WANG Guo1, XIA Kaizhe1, SHI Kai1 . Trajectory Optimization Method of Freight Suspended Monorail Train in Complex Environment[J]. Journal of Shanghai Jiaotong University, 0 : 1 . DOI: 10.16183/j.cnki.jsjtu.2024.412
/
〈 |
|
〉 |