Research On The Control Strategy Of Freight Train Based On Simulations

In recent years, with the rapid development of transportation, energy-efficient optimization control technology of freight trains has been widely concerned. There are two aspects of freight trains energy-efficient optimization:the optimization of energy saving speed curve and the control algorithms of train operation velocity curve tracking. This thesis mainly probes the control algorithms of train operation velocity curve tracking. Based on the dynamic model of freight trains, fuzzy controller and Proportion Integration Differentiation (PID) controller, dynamic matrix predictive controller and Proportion Integration (PI) controller which applied to Automatic Train Operation System (ATO) of freight trains are compared in the simulation of Matlab. Comparing the PID controller with fuzzy controller, the simulation results show that the fuzzy controller has a better effect on speed-tracking performance, robustness and energy saving than PID controller. Compared with PI control algorithm, the dynamic matrix predictive control algorithm has distinct advantages in terms of speed curve tracking, outside uncertain interference and energy efficiency. The main contribution of this paper is to introduce dynamic matrix predictive control to freight train operation velocity curve tracking. Its control performance and energy saving effect are much better than the PI control strategy.The main works of this thesis are listed as follows:Firstly, the author makes a detailed study on the control process, the mathematical model and energy model of the HXD3ac drive electric locomotive, which will lay the foundation for the train speed tracking controller design.Secondly, the author designs a train speed tracking controller based on fuzzy theory and technology. It carries out detailed simulation under different operating conditions of fuzzy controller and PID controller with MATLAB.Thirdly, the PID control and fuzzy control has many defects, such as the train time-delay, and cannot use the given ramp and tracking curve effectively. As predictive control algorithm has great potential in solving these problems, this paper introduces it into the train speed tracking. In addition, the comparison between the simulation of the dynamic matrix predictive control algorithm and PI control algorithm under the different working conditions such as ordinary ramp, random resistance and undulating track has been made.Finally, author optimizes the energy saving speed curve under the steep inclines, steep declines and steep hill on condition that time constraints and the speed limit in this thesis. It studies on the speed tracking performance and energy saving effect of the dynamic matrix predictive control algorithm under these special conditions.