首页|紧急制动工况下虚拟轨道列车车间铰接力研究

紧急制动工况下虚拟轨道列车车间铰接力研究

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围绕一种新型多轴铰接式城市轨道交通工具——虚拟轨道列车，针对路面附着条件变化会造成轮胎制动力不足、车轮抱死和车间铰接力增大的问题，提出了一种考虑路面附着系数的列车自动紧急制动策略。首先，采用扩展卡尔曼滤波和模型预测控制原理设计了上层控制器，基于实时估计的路面附着系数、列车制动舒适性和安全性，确定列车期望制动加速度;其次，基于轴荷比例分配原则和PID反馈补偿控制原理设计了下层控制器，根据列车期望制动加速度确定列车各轮胎的制动力矩;最后，搭建了Matlab/Simulink与Trucksim联合仿真平台，研究了列车制动过程中车间铰接力变化情况。结果表明，列车载重、制动初始车速以及路面附着系数变化对车间最大铰接力有影响;本文的制动策略具有良好的鲁棒性，在不同工况下能够有效防止车轮抱死、减小最大铰接力，提高列车制动过程中的舒适性和安全性。
Research on Vehicle Articulated Forces of Virtual Track Train under Emergency Braking Conditions
For the problems such as the lack of tire braking force,the wheel locking-up and the increase of articulated forces between the vehicles caused by the change of road adhesion condition,an automatic emergency braking strategy of the virtual rail train,which is a new multi-axle articulated urban rail transportation vehicle,is proposed considering road adhesion coefficient. The proposed strategy consists of two-layer controllers. Firstly,the upper controller is designed by extended Kalman filter and model predictive control,and the desired braking acceleration of the train is determined according to the real-time estimated road adhesion coefficient and the braking performances of comfort and safety. Secondly,the lower controller is designed by the principles of load proportion distribution and PID feedback com-pensation control,and the braking torques of train tires are determined based on the desired braking ac-celeration of the train. Finally,the co-simulation platform of Matlab/Simulink and Trucksim is built to research the vehicle articulated forces of virtual rail train under emergency braking conditions. The re-sults show that the variations of train load,initial braking speed of the train and road adhesion coefficient affect the maximum articulated force between the vehicles. The proposed strategy processes good ro-bustness. It can prevent the wheels locking-up,reduce the maximum articulated force between the vehi-cles and improve the braking performances of comfort and safety under various conditions.

virtual rail trainarticulated forces between the vehiclesautomatic emergency brakingroad adhesion coefficient estimationextended Kalman filtermodel predictive control

王谭明、杨蔡进、赵煜、徐菁、蔡立雅、张卫华

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西南交通大学轨道交通运载系统全国重点实验室,成都 610031

盐城工学院机械优集学院,盐城 224051

虚拟轨道列车 车间铰接力 自动紧急制动 路面附着系数估计 扩展卡尔曼滤波 模型预测控制

国家重点研发计划四川省科技计划项目

2018YFB101603-062020JDRC0008

2024

10.6052/1672-6553-2024-005

动力学与控制学报
中国力学学会　湖南大学

动力学与控制学报

CSTPCD
影响因子：0.446
ISSN：1672-6553
年,卷(期)：2024.22(8)