Title :
Optimal driving strategy for traction energy saving on DC suburban railways
Author :
Bocharnikov, Y.V. ; Tobias, A.M. ; Roberts, C. ; Hillmansen, S. ; Goodman, C.J.
Author_Institution :
Univ. of Birmingham, Birmingham
Abstract :
Energy saving on electrified railways has been studied for many years and the technical solution is usually provided by a combination of driving strategy (e.g. coasting), regenerative braking and energy storage systems. An alternative approach is for the driver (or automatic train operation system if fitted) to manage energy consumption more efficiently. A formal method for optimising traction energy consumption during a single-train journey by trading-off reductions in energy against increases in running time has been demonstrated. The balance between saving energy and running faster has been investigated by designing a fitness function with variable weightings. Energy savings were found, both qualitatively and quantitatively, to be affected by acceleration and braking rates, and, by running a series of simulations in parallel with a genetic algorithm search method, the fitness function was used to identify optimal train trajectories. The influence of the fitness function representation on the search results was also explored.
Keywords :
energy conservation; energy storage; genetic algorithms; railway electrification; DC suburban railways; acceleration rate; automatic train operation system; braking rate; electrified railways; energy storage systems; fitness function; genetic algorithm search; optimal driving strategy; regenerative braking; traction energy consumption; traction energy saving;
Journal_Title :
Electric Power Applications, IET
DOI :
10.1049/iet-epa:20070005