Optimize Energy of Train Simulation with Track Slope Data

This study aims to establish equations for energy consumptions of Taiwan Railways Administration (TRA) trains in operation considering the variations of slope to determine the traction energy cost (TEC). Where railway transportation has been one of the important means of transport for mankind, since TRA became electrified the parameters for train operations have been able to be accurately recorded. The equations for overall energy consumption and resistance parameters are completed for the overall energy consumption of TRA trains and resistance to them to simulate the operation of the whole train model. The inputs of different conditions of trains and track sections are then analyzed for energy use, as the energy use by train travel is obvious. That by the behavior of energy use, can be divided in three conditions for analysis which is acceleration, coasting and deceleration. In the analysis of the energy in the journey, the variation of its consumption is subject to multiple factors because of the difference in operation model and the variation in the track slope data. In view of decreasing unnecessary energy consumption, the equations for train energy consumption and the track parameters are substituted in the teaching-learning-based optimization (TLBO) technique, which can compute the optimal results fast. The optimal results being incorporated in the trains can help reduce unnecessary energy consumption and errors by human operations and arrive at the destination on schedule. By the equations for energy consumption, train parameters, and TLBO, this study proved to be able to reduce energy use as well as ensure of Top Transport Time Expenditure (TTE) of the trains.

Language

  • English

Media Info

  • Media Type: Web
  • Features: References;
  • Pagination: pp 590-597
  • Monograph Title: 18th International IEEE Conference on Intelligent Transportation Systems (ITSC 2015)

Subject/Index Terms

Filing Info

  • Accession Number: 01603018
  • Record Type: Publication
  • ISBN: 9781467365956
  • Files: TRIS
  • Created Date: May 2 2016 3:20PM