Electrified railways are becoming a popular transport medium and these consume a large amount of electrical energy.Environmental concerns demand reduction in energy use and peak power demand of railway systems.Further...Electrified railways are becoming a popular transport medium and these consume a large amount of electrical energy.Environmental concerns demand reduction in energy use and peak power demand of railway systems.Furthermore,high transmission losses in DC railway systems make local storage of energy an increasingly attractive option.An optimisation framework based on genetic algorithms is developed to optimise a DC electric rail network in terms of a comprehensive set of decision variables including storage size,charge/discharge power limits,timetable and train driving style/trajectory to maximise benefits of energy storage in reducing railway peak power and energy consumption.Experimental results for the considered real-world networks show a reduction of energy consumption in the range 15%–30%depending on the train driving style,and reduced power peaks.展开更多
This paper studies the integration of the control system and entertainment on board of train wagons. Both the control and entertainment loads are implemented on top of Gigabit Ethernet, each with a dedicated controlle...This paper studies the integration of the control system and entertainment on board of train wagons. Both the control and entertainment loads are implemented on top of Gigabit Ethernet, each with a dedicated controller/server. The control load has mixed sampling periods. It is proven that this system can tolerate the failure of one controller in one wagon. In a two wagon scenario, fault tolerance at the controller level is studied, and simulation results show that the system can tolerate the failure of 3 controllers. The system is successful in meeting the packet end-to-end delay with zero packet loss in all OPNET simulated scenarios. The maximum permissible entertainment load is determined for the fault tolerant scenarios.展开更多
文摘Electrified railways are becoming a popular transport medium and these consume a large amount of electrical energy.Environmental concerns demand reduction in energy use and peak power demand of railway systems.Furthermore,high transmission losses in DC railway systems make local storage of energy an increasingly attractive option.An optimisation framework based on genetic algorithms is developed to optimise a DC electric rail network in terms of a comprehensive set of decision variables including storage size,charge/discharge power limits,timetable and train driving style/trajectory to maximise benefits of energy storage in reducing railway peak power and energy consumption.Experimental results for the considered real-world networks show a reduction of energy consumption in the range 15%–30%depending on the train driving style,and reduced power peaks.
文摘This paper studies the integration of the control system and entertainment on board of train wagons. Both the control and entertainment loads are implemented on top of Gigabit Ethernet, each with a dedicated controller/server. The control load has mixed sampling periods. It is proven that this system can tolerate the failure of one controller in one wagon. In a two wagon scenario, fault tolerance at the controller level is studied, and simulation results show that the system can tolerate the failure of 3 controllers. The system is successful in meeting the packet end-to-end delay with zero packet loss in all OPNET simulated scenarios. The maximum permissible entertainment load is determined for the fault tolerant scenarios.
