地铁列车精确停车算法研究

Research on Precisive Parking Algorithm for Metro Train

地铁列车停车精度是列车自动驾驶系统性能的重要指标。结合车辆参数、列车冲击、电空转换等性能建立了列车制动模型,并提出了利用在线识别的方式对每一列车的空气制动参数进行自学习,解决了不同列车因空气制动变化导致的制动异常问题,可较好地提高列车自动驾驶舒适性和精确停车模型的鲁棒性。通过仿真和实际工程项目结果分析,所提出的制动模型可保证列车的停车精度达到±0.25 m。

Metro train parking precision is an important indicator of train automatic control system.A train control model is established based on the performance of vehicle parameters,train jerk,electro-pneumatic conversion,and a self-learning based on online recognition of the air braking parameters of each train.The braking abnormality problem caused by air braking changes in different trains is solved,and the comfort of automated driving and robustness of precisive parking model can be well improved.Through simulation and analysis of actual engineering project results,the proposed braking model can ensure train parking precision within±0.25 m.