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Recent Patents on Mechanical Engineering

Author(s): Lingzhi Yi, Cheng Xie*, Yahui Wang, Jiangyong Liu, Chuyang Yi and Wenbo Jiang

DOI: 10.2174/2212797616666230622143121

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Energy Saving Optimal Operation Strategy of Freight Trains under Complex Scenarios

Page: [237 - 250] Pages: 14

  • * (Excluding Mailing and Handling)

Abstract

Background: For the optimization of energy-saving driving of freight trains in complex operating environments, the use of reasonable train maneuvering methods can largely reduce the energy consumption of train traction. Recent patents on energy-efficient maneuvering strategies for complex scenarios of freight trains have been researched.

Objective: Using the receding horizon algorithm and the improved NSGA-II algorithm to solve the target speed curve of freight trains to cope with the complex and changing operating environment, and to explore the recent patents of energy-saving maneuvering strategies for freight trains and methods.

Methods: The recent patents of energy-efficient maneuvering strategies for freight trains in complex scenarios are investigated in this research. A multi-objective optimization model for freight train maneuvering with electrical phasing was developed with the objectives of reducing the traction energy consumption and running time of the train. A method for determining the optimal operating conditions of freight trains under complex line conditions is proposed. The offline optimization of the target speed curve under the electrical phasing constraints of freight trains and the online adjustment under the temporary speed restriction (TSR) are achieved by using the RH-INSGA-II (receding horizon-improved NSGA- II) algorithm.

Results: Combined with an actual freight railroad line data as an example, simulation experiments were conducted and verified with HXD1 electric locomotive hauling 50 C80 wagons.

Conclusion: The speed curve considering the split-phase constraint can effectively reduce the traction energy consumption. The electrical split-phase constraint affects the whole speed optimization process, not only the speed curve at the split-phase zone. Although the traction energy consumption is increased with the addition of the TSR on the line, the RH-INSGA-II algorithm dynamically changes the sequence of optimal train maneuvering conditions according to the planned train running time in order to avoid further amplification of the late train time.

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