Modeling and optimizing energy‐efficient manual driving on high‐speed lines

This paper presents a simulation-based model for manual driving strategies that will minimize energy consumption for high-speed trains. Specific characteristics of both high-speed lines (HSLs) and manual driving strategies are considered in order to obtain achievable designs that can be tested on commercial services. The proposed design model calculates a list of efficient high-level commands to be systematically executed by the driver on an HSL along the trip. The design is based on a detailed simulation model of the train's motion (taking into account track and train characteristics and operational constraints), combined with a genetic algorithm to select the best driving. Continuous control solution by mathematical optimization is avoided, as it is not an appropriate reference for manual driving in HSL. The validation of the simulation model is focused on running resistance, tractive/braking efficiencies, and consumption of auxiliary equipment, and shows differences between real measurements and simulated results which are lower than 2% both in run time and energy consumption. Finally, a real case is presented in which the proposed model was used to design efficient driving strategies that were subsequently implemented on commercial services along the Spanish HSL Madrid–Barcelona in both directions, measuring average energy savings of 23 and 18%, respectively, when the efficient driving strategies were compared with measured standard manual driving. The future scope will be the application of this model to online recalculation of driving commands. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

[1]  K. Ichikawa Application of Optimization Theory for Bounded State Variable Problems to the Operation of Train , 1968 .

[2]  Tin Kin Ho,et al.  Coast control for mass rapid transit railways with searching methods , 2004 .

[3]  Asunción P. Cucala,et al.  Efficient Design of Automatic Train Operation Speed Profiles with On Board Energy Storage Devices , 2010 .

[4]  Georges Bastin,et al.  Traffic modeling and state feedback control for metro lines , 1991 .

[5]  Baigen Cai,et al.  Automatic Train Control System Development and Simulation for High-Speed Railways , 2010, IEEE Circuits and Systems Magazine.

[6]  A Nasri,et al.  Timetable optimization for maximum usage of regenerative energy of braking in electrical railway systems , 2010, SPEEDAM 2010.

[7]  Eugene Khmelnitsky,et al.  On an optimal control problem of train operation , 2000, IEEE Trans. Autom. Control..

[8]  Hee-Soo Hwang,et al.  Control strategy for optimal compromise between trip time and energy consumption in a high-speed railway , 1998, IEEE Trans. Syst. Man Cybern. Part A.

[9]  Thomas Albrecht,et al.  Dealing with operational constraints in energy efficient driving , 2010 .

[10]  Masafumi Miyatake,et al.  Optimization of Train Speed Profile for Minimum Energy Consumption , 2010 .

[11]  Chung-Fu Chang,et al.  Optimising train movements through coast control using genetic algorithms , 1997 .

[12]  Iakov M. Golovitcher Energy efficient control of rail vehicles , 2001, 2001 IEEE International Conference on Systems, Man and Cybernetics. e-Systems and e-Man for Cybernetics in Cyberspace (Cat.No.01CH37236).

[13]  Rongfang Rachel Liu,et al.  Energy-efficient operation of rail vehicles , 2003 .

[14]  Phil Howlett,et al.  Coasting boards vs optimalcontrol , 2010 .

[15]  Chao-Shun Chen,et al.  Design of optimal coasting speed for saving social cost in Mass Rapid Transit systems , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[16]  Andrew M. Tobias,et al.  Reduction of train and net energy consumption using genetic algorithms for Trajectory Optimisation , 2010 .

[17]  Tin Kin Ho,et al.  A review of simulation models for railway systems , 1998 .

[18]  Mehmet Turan Soylemez,et al.  Coasting point optimisation for mass rail transit lines using artificial neural networks and genetic algorithms , 2008 .

[19]  Clive Roberts,et al.  Optimal driving strategy for traction energy saving on DC suburban railways , 2007 .

[20]  Keiichiro Kondo Recent Energy Saving Technologies on Railway Traction Systems , 2010 .

[21]  Takafumi Koseki Technologies for Saving Energy in Railway Operation : General Discussion on Energy Issues Concerning Railway Technology , 2010 .

[22]  Phil G. Howlett,et al.  Local energy minimization in optimal train control , 2009, Autom..