Optimal design of metro automatic train operation speed profiles for reducing energy consumption

Abstract

Trains equipped with automatic train operation (ATO) systems are operated between stations according to the speed commands they receive from balises. These commands define a particular speed profile and running time, with associated energy usage (consumption). The design of speed profiles usually takes into account running times and comfort criteria, but not energy consumption criteria. In this article, a computer-aided procedure for the selection of optimal speed profiles, including energy consumption, which does not have an effect on running times, is presented. To this end, the equations and algorithms that define the train motion and ATO control have been modelled and implemented in a very detailed simulator. This simulator includes four independent modules (ATO, motor, train dynamics, and energy consumption), an automatic generator of every possible profile and a graphical assistant for the selection of speed commands in accordance with decision theory techniques. The results have been compared with measured data in order to adjust and validate the simulator. The implementation of this new procedure in the Madrid underground has led to a 13 per cent of energy saving. As a result, the decision has been taken to redesign all the ATO speed profiles on this underground.

Potential Benefits and Obstacles of Implementing Driverless Train Operation on the Tyne and Wear Metro: A Simulation Exercise

“…The automation of routine but high-stress driving tasks increases the safety of the system by reducing the potential for human error [4,19,25]. Individual train speed profiles can also be controlled precisely to minimise energy consumption for a given journey time, including real-time optimisation to take delays into account [2,34,35]. Finally, smoother changes of acceleration compared to manual control may increase the lifespan of wheelsets and traction/ braking equipment [19], and can also improve passenger comfort [22,36].…”

“…4.2, the simulation results assume allout running. The trade-off between journey times, energy consumption and overall capacity illustrated in Table 6 can be altered by changing the driving style, for example, by introducing coasting [34,35]. Likewise, increasing the maximum power rating of the higher performance rolling stock above that of the existing Metrocars will also alter this trade-off.…”

Review of energy-efficient train control and timetabling

“…The approach was applied on the Madrid Metro line 3 in Spain resulting on average in 13% energy savings compared to the previous ATO design without affecting the scheduled running times. Domínguez et al (2012) extended the simulation model of Domínguez et al (2011) by considering the energy in the substations to include regenerative braking. Using the same method as before the model was also tested on the Madrid Metro line 3.…”

“…Results showed 7% energy saving compared to normal real-time operation. Domínguez et al (2011) developed a simulation model for the Madrid metro system driven by ATO. The simulation model includes four independent modules (ATO, engine, train dynamics, and energy consumption).…”

An Integrated Energy-Efficient Operation Methodology for Metro Systems Based on a Real Case of Shanghai Metro Line One

“…The operation strategy of eco-driving is to optimize the speed profile of each train, while the utilization of regenerative braking energy is for one train to re-use the energy generated by the braking of other trains. The first topic has been well studied by many researchers [3][4][5][6][7][8][9][10][11][12][13][14][15], while the latter is a rather new approach. It is based on the practice that the acceleration process consumes energy from the power supply network whereas the braking process returns energy to the supply network.…”