Online optimization for the multi-objective operation of electric multiple units based speed limits curve

The electric multiple units (EMU) provide a transport service in the dynamical running environment, which should meet the requirements of safety, punctuality, precise train stopping, energy conservation and comfort simultaneously. However, since pervious manual operation method of EMU is mainly base...

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Vydáno v:Proceeding of the 11th World Congress on Intelligent Control and Automation s. 6172 - 6177
Hlavní autoři: Hui Yang, Hong-En Liu, Ya-Ting Fu
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2014
Témata:
Delays
Electric multiple units
Force
Indexes
Multi-objective online optimization
Operation strategy
Optimization
Particle swarm optimization algorithm
Real-time systems
Resistance
Safety
Speed limit
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Shrnutí:The electric multiple units (EMU) provide a transport service in the dynamical running environment, which should meet the requirements of safety, punctuality, precise train stopping, energy conservation and comfort simultaneously. However, since pervious manual operation method of EMU is mainly based on a given V-S curve (velocity versus position curve) and drivers' experience, it cannot meet the multi-objective operation requirements in real time. In order to improve the operation strategy, this paper develops a multi-objective online optimization model for the EMU operation based on speed limit curve. Then, we optimize the operation strategy using a modified multi-objective particle swarm optimization algorithm on line, so as to obtain the Pareto optimal solution set. Further, based on the delay state of EMU running process, we pick out the optimal operation strategy from the Pareto set. Finally, the running process of the EMU operated on the optimal operation strategy can satisfy the multi-objective requirements. And the experimental results on the field data of CRH380AL (China railway high-speed EMU type-380AL) running process show the real time effectiveness of the proposed approach.
DOI:10.1109/WCICA.2014.7053778