• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 25 Issue 2
Mar.  2012
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Article Contents
LU Qiheng, FENG Xiaoyun, WANG Qingyuan. Energy-Saving Optimal Control of Following Trains Based on Genetic Algorithm[J]. Journal of Southwest Jiaotong University, 2012, 25(2): 265-270. doi: 10.3969/j.issn.0258-2724.2012.02.016
Citation: LU Qiheng, FENG Xiaoyun, WANG Qingyuan. Energy-Saving Optimal Control of Following Trains Based on Genetic Algorithm[J]. Journal of Southwest Jiaotong University, 2012, 25(2): 265-270. doi: 10.3969/j.issn.0258-2724.2012.02.016

Energy-Saving Optimal Control of Following Trains Based on Genetic Algorithm

doi: 10.3969/j.issn.0258-2724.2012.02.016
  • Received Date: 05 Apr 2010
  • Rev Recd Date: 27 Oct 2010
  • Publish Date: 25 Apr 2012
  • In order to study the optimum operating strategy for energy saving of the following train in a following operation, the static speed constraints of the trains and the dynamic speed constraints of the following train were put forward under a four-aspect fixed autoblock system. On this basis, an energy-saving optimal operation model of the following train was created taking the train control notch and the corresponding train position as control variables. With the help of the external punishment function, the model was solved by the changeable chromosome length multi-objective genetic algorithm (GA). The shifting strategy of the train control notch was optimized using the chromosome length mutation operator of GA to determine the change times of the train control notch during the whole trip. The simulation result from a four-aspect fixed autoblock system simulation platform shows that the method can reduce the energy consumption and trip time error of the following train by 4.3% and 1.7%, respectively, on the premise of safety and punctuality.

     

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