Optimisation of total traction current based on niche improved particle swarm algorithms

Due to the short distance between stations in DC mass transit systems, the trains accelerate and decelerate frequently with high traction current. If numerous trains are accelerating simultaneously, an extremely high traction current peak occurs. This current will have a great impact on the power su...

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Bibliographic Details
Published in:IET electrical systems in transportation 2016-12, Vol.6 (4), p.253-260
Main Authors: Guoxin, Li, Guifu, Du, Chonglin, Wang
Format: Article
Language:English
Subjects:
Algorithms
Deceleration
Mass transit
niche improved particle swarm algorithms
Optimization
particle swarm optimisation
Power supplies
power supply system
Research Article
Stations
total maximum traction current value reduction
total traction current optimisation
Traction
traction power supplies
Transportation
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Summary:Due to the short distance between stations in DC mass transit systems, the trains accelerate and decelerate frequently with high traction current. If numerous trains are accelerating simultaneously, an extremely high traction current peak occurs. This current will have a great impact on the power supply system, and cause elevated rail potential in reflow system. This study presents an optimal model on traction current by adjusting the train's dwell time, reducing the coincidence degree when multi-train accelerate. Niche improved particle swarm algorithms for traction current optimisation is constructed. Optimised calculation results from the simulation of actual line show that the optimisation can significantly reduce the total maximum traction current value.
ISSN:2042-9738
2042-9746
2042-9746
DOI:10.1049/iet-est.2015.0038