Research Note: Energy Saving in Railway Transportation using Particle Swarm Optimization

Document Type : Scientific - Research

Abstract

Increasing trend to use railway transport as one pillar of transporting passengers and goods in one hand, and daily reduction of available oil resources and as a result fuel reduction and also solving of pollution environmental problem in other hand illustrate importance of more studies and researches in this domain. Due to optimized energy consumption in railway industry that is very important, we can use optimization algorithms. One of intelligent and capable algorithms in optimization problems is Particle Swarm Optimization (PSO) algorithm as one of the newest optimization algorithms. Besides suggesting a comprehensive model of train movement dynamics and its fuel consumption, a novel and applicable method to save energy using PSO algorithm has also been suggested in this paper. To illustrate the proposed method more clearly, some applicable scenarios with their simulation results are considered and analyzed during the study. At the end, some worthwhile suggestions for future researches are presented.

Keywords


  1.  

    -Cheng J. and  Howlett, P. (1992)  "Application of Critical Velocities to the minimisation of fFuel consumption in the control of trains",  Automatica, vol 28,pp165-169.

    -Howlett, P., Milroy I. and Pudney, P. (1994), "Energy – Efficient Train Control", Control Eng. Practice, Vol.2, No. 2.

    -Kennedy, J.  and Eberhart, R.(1995)  "Particle swarm optimization", IEEE Conference.

    -Khanbaghi, M. and Malhame, R.P. (1994) "Reducing travel energy costs for a subway train via fuzzy logic controls", Intelligent Control Symposium.

    -Qunzhan, L. and Bing, T. (2009)  "Energy saving train control for urban railway train with multi-population genetic algorithm ", Information Technology and Applications, IFITA '09 Conference.

    -Wei, L.,Qunzhan, L. and Bing, T. (2009), "Energy saving train control for urban railway train with multi-population genetic algorithm", International Forum on Information Technology and Applications.

     

    -Wai, R. J., Huang, Y.C. and Chen, Y. C. (2012) " Design of intelligent long-term load forecasting with fuzzy neural network and particle swarm optimization", Machine Learning and Cybernetics (ICMLC), Conference.

    1. آزادی، سامان ، میرآبادی، احمد و صندیدزاده، محمد علی (1385) "بهینه سازی مصرف انرژی قطار با استفاده از الگوریتم ژنتیک"، هفتمین کنفرانس مهندسی حمل و نقل و ترافیک ایران.