城市轨道交通列车控制系统多基于固定参数算法，面对环境变化时存在制动不准、停车位置偏差等问题,从而增加碰撞风险，直接威胁列车运行安全和乘客舒适度。针对既有线路自动控制系统实时性和准确性不足等问题，提出列控系统智能化升级方案，首先通过参数拟合建立精确列车动力学模型，然后应用滑模自适应鲁棒控制策略进行实时调整。通过对北京地铁5号线的仿真验证，对列车模型和车载控制器的优化算法进行了制动性能指标计算，停车精度优化比例达91.36%。研究结果表明：所提出的优化措施在提升制动性能方面的有效性，在城市轨道交通系统中具有重要的应用价值和实用意义。

The train control system of urban rail transit is mostly based on fixed parameter algorithm, which has problems such as inaccurate braking and deviation of parking position in the face of environmental changes, thus increasing the risk of collision and directly threatening the safety of train operation and passenger comfort. Aiming at the shortage of real-time and accuracy of the existing automatic control system, an intelligent upgrade scheme of train control system is proposed. Firstly, an accurate train dynamics model is established by parameter fitting, and then a sliding mode adaptive robust control strategy is used to adjust the train control system in real time. Through the simulation of Beijing Metro Line 5, the braking performance index of the train model and the optimization algorithm of the on-board controller are calculated, and the optimization ratio of the parking accuracy reaches 91.36%. The results show that the proposed optimization measures are effective in improving braking performance and have important application value and practical significance in urban rail transit system.

北京市地铁运营有限公司2023年科研计划项目(2023000501000003)