Open AccessOptimisation of total traction current based on niche improved particle swarm algorithms
Author(s) -
Guoxin Li,
Guifu Du,
Chonglin Wang
Publication year - 2016
Publication title -
iet electrical systems in transportation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.588
H-Index - 26
eISSN - 2042-9746
pISSN - 2042-9738
DOI - 10.1049/iet-est.2015.0038
Subject(s) - particle swarm optimization , niche , traction (geology) , current (fluid) , algorithm , swarm behaviour , computer science , mathematical optimization , materials science , engineering , mathematics , mechanical engineering , biology , ecology , electrical engineering
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.