Driving and operation strategies for traction-energy saving in mass rapid transit systems

Malavasi, Gabriele; Palleschi, P; Ricci, Stefano

doi:10.1177/2041301710395077

Cited by 31 publications

(14 citation statements)

References 9 publications

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“…The computation time of the method reached a reasonable level, which made it possible to achieve online optimization. Malavasi et al [62] formulated two models to estimate the energy saving potential on mass rapid transit systems. The first model was very useful for analyzing the energy, and the second one aimed at estimating consumptions of a mass rapid transit system within a period of time.…”

Section: B Literature Overviewmentioning

confidence: 99%

A Survey on Energy-Efficient Train Operation for Urban Rail Transit

Yang

Ning

et al. 2016

IEEE Trans. Intell. Transport. Syst.

320

133

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Due to rising energy prices and environmental concerns, the energy efficiency of urban rail transit has attracted much attention from both researchers and practitioners in recent years. Timetable optimization and energy-efficient driving, as two mainly used train operation methods in relation to the tractive energy saving, make major contributions in reducing the energy consumption that has been studied for a long time. Generally speaking, timetable optimization synchronizes the accelerating and braking actions of trains to maximize the utilization of regenerative energy, and energy-efficient driving optimizes the speed profile at each section to minimize the tractive energy consumption. In this paper, we present a fully comprehensive survey on energy-efficient train operation for urban rail transit. First, a general energy consumption distribution of urban rail trains is described. Second, the current literature on timetable optimization and energy-efficient driving is reviewed. Finally, according to the review work, it is concluded that the integrated optimization method jointly optimizing the timetable and speed profile has become a new tendency and ought to be paid more attention in future research.

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Section: B Literature Overviewmentioning

confidence: 99%

A Survey on Energy-Efficient Train Operation for Urban Rail Transit

Yang

Ning

et al. 2016

IEEE Trans. Intell. Transport. Syst.

320

133

View full text Add to dashboard Cite

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“…Energy is the focus and main cost for metro system operators. Most energy is consumed in train operations [25,26], and thus obtaining an energy-efficient train timetable receives considerable attention [17,18,27]. Note that energy is affected by the travel time in the segment, and the segment travel time is determined by the arrival and departure times at adjacent stations, that is, the timetable.…”

Section: Operator-oriented Objectivesmentioning

confidence: 99%

Metro Timetabling for Time-Varying Passenger Demand and Congestion at Stations

Huang

Schonfeld

2018

Journal of Advanced Transportation

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For the train timetabling problem (TTP) in a metro system, the operator-oriented and passenger-oriented objectives are both important but partly conflicting. This paper aims to minimize both objectives by considering frequency (in the line planning stage) and train cost (in the vehicle scheduling stage). Time-varying passenger demand and train capacity are considered in a nonsmooth, nonconvex programming model, which is transformed into a mixed integer programming model with a discrete time-space graph (DTSG). A novel dwell time determining process considering congestion at stations is proposed, which turns the dwell times into dependent variables. In the solution approach, we decompose the TTP into a subproblem for optimizing segment travel times (OST) and a subproblem for optimizing departure headways from the shunting yard (OH). Branch-and-bound and frequency determining algorithms are designed to solve OST. A novel rolling optimization algorithm is designed to solve OH. The numerical experiments include case studies on a short metro line and Beijing Metro Line 4, as well as sensitivity analyses. The results demonstrate the predictive ability of the model, verify the effectiveness and efficiency of the proposed approach, and provide practical insights for different scenarios, which can be used for decision-making support in daily operations.

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“…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].…”

Section: Automatic Train Operation (Goa 2)mentioning

confidence: 99%

“…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.…”

Section: Energy Consumptionmentioning

confidence: 99%

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

et al. 2016

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Metro systems around the world have many differences in their design and operation, one aspect of which is the level of automation. The most advanced technology available allows for unattended train operation with no staff on-board, which can bring a number of benefits. As a result, this is becoming increasingly common for new-build metro systems (such as the Dubai Metro), as well as for upgrades of traditional driver-led systems (such as Paris Métro Line 1). This paper uses the Tyne and Wear Metro as a case study to highlight the potential benefits and obstacles of implementing driverless trains on an existing metro system. This investigation has two parts: a review of the challenges of implementing increasing levels of automation for the existing Metro infrastructure and a simulation exercise to compare automatic train operation with manual driving on the core section of the Metro network. The results of the simulation exercise show that significant increases in the capacity of the Tyne and Wear Metro system are possible when automatic train operation is implemented in conjunction with resignalling. However, low adhesion conditions represent a significant risk to achieving this capacity increase reliably, and additional measures to mitigate low adhesion conditions would be required. The study also discusses the infrastructure upgrades required to convert an existing system to unattended train operation. The most significant obstacle for the Metro is that it mostly runs at ground level, with some sections shared with main line services. The costs associated with securing the tracks and ensuring compatibility with main line trains mean that the Metro is not a particularly promising application for driverless train operation at this time. Nonetheless, the issues discussed in the paper are very much relevant for other metro systems, and the methodology of this study is easily transferrable.

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Driving and operation strategies for traction-energy saving in mass rapid transit systems

Cited by 31 publications

References 9 publications

A Survey on Energy-Efficient Train Operation for Urban Rail Transit

A Survey on Energy-Efficient Train Operation for Urban Rail Transit

Metro Timetabling for Time-Varying Passenger Demand and Congestion at Stations

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

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