Research on Trajectory Tracking of Heavy-Haul Trains Based on Model Predictive Control
[Purposes]To enhance the safety,stability,and energy efficiency of overloaded trains and re-duce the coupling force between cars,this paper proposes a trajectory tracking method for overloaded trains based on model predictive control.[Methods]Firstly,a multi-mass dynamic model of overloaded trains considering the coupling force between vehicles is established.Then,the longitudinal impulse of the train,train energy consumption,and speed tracking errors are transformed into problems conforming to the model predictive control framework.Finally,a speed tracking controller based on model predictive control algorithm is designed,with the target speed curve as input and train control force as output.[Find-ings]This paper proposes a model predictive control algorithm aimed at improving the accuracy of track-ing the reference speed curve,reducing the impulse of the coupling force,and lowering train energy con-sumption.[Conclusions]Simulation analyses are conducted based on actual vehicle and track data to ex-amine the effects of different prediction step lengths and weight coefficients on control performance.Through comparative simulation experiments,the effectiveness of the proposed algorithm is verified,demonstrating its ability to enhance the accuracy of train speed tracking,reduce coupling force impulse,and decrease train energy consumption.
heavy-haul trainsmulti-particle modelautonomous train drivingmodel predictive control
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