Optimal driving strategy for traction energy saving on DC suburban railways

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Optimal driving strategy for traction energy saving on DC suburban railways. / Bocharnikov, Yury; Roberts, Clive; Hillmansen, Stuart; Tobias, Andrew; Goodman, Colin.

In: IET Electric Power Applications, Vol. 1, No. 5, 01.01.2007, p. 675-682.

Research output: Contribution to journalArticle

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@article{5fc2d05b69c24fbb921ad6ad42b5627e,
title = "Optimal driving strategy for traction energy saving on DC suburban railways",
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.",
author = "Yury Bocharnikov and Clive Roberts and Stuart Hillmansen and Andrew Tobias and Colin Goodman",
year = "2007",
month = jan,
day = "1",
doi = "10.1049/iet-epa:20070005",
language = "English",
volume = "1",
pages = "675--682",
journal = "IET Electric Power Applications",
issn = "0143-7038",
publisher = "Institution of Engineering and Technology",
number = "5",

}

RIS

TY - JOUR

T1 - Optimal driving strategy for traction energy saving on DC suburban railways

AU - Bocharnikov, Yury

AU - Roberts, Clive

AU - Hillmansen, Stuart

AU - Tobias, Andrew

AU - Goodman, Colin

PY - 2007/1/1

Y1 - 2007/1/1

N2 - 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.

AB - 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.

U2 - 10.1049/iet-epa:20070005

DO - 10.1049/iet-epa:20070005

M3 - Article

VL - 1

SP - 675

EP - 682

JO - IET Electric Power Applications

JF - IET Electric Power Applications

SN - 0143-7038

IS - 5

ER -