Potential for metro rail energy savings and emissions reduction via eco-driving

Yuan, Wenqiao; Frey, H. Christopher

doi:10.1016/j.apenergy.2020.114944

Cited by 25 publications

(12 citation statements)

References 30 publications

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“…Yuan et al illustrate that train operations can be varied to reduce energy use and emissions while adhering to a schedule. 33 For hotspots where the modification of train operation may be unachievable, emission reduction interventions such as alternate fuels and retrofitted exhaust aftertreatment technology may be effective. The combined effect of operation, fuels, and technology on FUERs and hotspots is recommended for further evaluation.…”

Section: ■ Methodsmentioning

confidence: 51%

“…Scheduling constraints, speed limits, rail traffic, delays, and existing track infrastructure would need to be considered in designing a modified train trajectory that reduces the number of hotspots. Yuan et al illustrate that train operations can be varied to reduce energy use and emissions while adhering to a schedule …”

Section: Resultsmentioning

confidence: 99%

“…Several studies demonstrated methods to modify a 1 Hz train activity and were focused on reductions in energy use for a given trip. − Frey et al ,,, and Vojtisek-Lom et al measured real-world 1 Hz FUERs for passenger rail service . To quantify spatial variability in FUERs, Gould and Niemeier apportioned annual aggregated fuel use data to local track segments .…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service

Rastogi

Frey

2021

Environ. Sci. Technol.

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Spatially varying diesel locomotive fuel use and emission rates (FUERs) are needed to accurately quantify local emission hotspots and their health impacts. However, existing locomotive FUER data are typically not spatially resolved or representative of real-world locomotive operation. Therefore, existing data are of limited use in quantifying the spatial variability in real-world FUERs. The objectives of this work are to quantify spatial variability in locomotive FUERs and identify factors differentiating hotspots from non-hotspots. FUERs were measured based on real-world measurements conducted for the Piedmont passenger rail service using a portable emission measurement system. FUERs were quantified based on 0.25 mile track segments on the Piedmont route. Hotspots were defined as segments in the top quintile of segment-average FUERs. On average, hotspots contributed 40–50% to trip fuel use and emissions. Hotspots were typically associated with low-to-medium speed, and high acceleration and grade. In contrast, non-hotspots were associated with high speed, and low acceleration and grade. Hotspots were typically located near populated areas and, thus, may exacerbate air pollutant exposure. The method demonstrated here can be applied to other passenger train services to assess key trends in hotspot locations and factors that explain the occurrence of hotspots.

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Section: ■ Methodsmentioning

confidence: 51%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service

Rastogi

Frey

2021

Environ. Sci. Technol.

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“…Among the possible strategies that can be used to reduce rail energy consumption (low consumption engines, energy recovery systems, etc. ), energy-efficient driving, or eco-driving, is one of the most promising [6][7][8]. This lies in the following strengths: (1) It can be adopted even with current trains (rolling stock need not be changed); (2) it requires low investments (the cost of the information system needed to implement the strategy is very low compared to the procurement cost of the train); (3) the time needed for its implementation can be low because the system does not require any intervention on the railway infrastructure or rolling stock.…”

Section: Introductionmentioning

confidence: 99%

“…The application of the proposed model is limited to frequency-based lines; other models proposed in the literature (see, for instance [8,35]) must be used for schedule-based services. Clearly, the application of the model to other metro lines requires the recalibration of time and consumption functions and the construction of the corresponding simulation models.…”

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confidence: 99%

A Simulation Approach for Optimising Energy-Efficient Driving Speed Profiles in Metro Lines

et al. 2020

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We propose a model for optimising driving speed profiles on metro lines to reduce traction energy consumption. The model optimises the cruising speed to be maintained on each section between two stations; the functions that link the cruising speed to the travel time on the section and the corresponding energy consumption are built using microscopic railway simulation software. In addition to formulating an optimisation model and its resolution through a gradient algorithm, the problem is also solved by using a simulation model and the corresponding optimisation module, with which stochastic factors may be included in the problem. The results are promising and show that traction energy savings of over 25% compared to non-optimised operations may be achieved.

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Characteristics and assessment of the electricity consumption of metro systems: A case study of Tianjin, China

Yu,

You,

et al. 2023

Energy Science & Engineering

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Owing to the complexity of metros, the energy consumption characteristics of metro systems exhibit variability and the energy‐saving management of the systems encounters challenges. To encapsulate the essential characteristics of energy usage and to objectively assess the energy performance of metro systems, this study presents a generalized framework and applies it to a case study conducted in Tianjin. The study also employs correlation analysis to investigate the applicability of the indicators relevant to ridership. The results indicate that the monthly traction electricity consumption exhibits slight variation, while station electricity usage demonstrates substantial fluctuation with seasonal changes. For Tianjin Metro, the passenger factor hardly shows any effect on the electricity use of metro lines. The median value of traction electricity use is approximately 2.0 kWh/(car‐km) and that of the average annual station electricity use of underground lines ranges from 95 to 155 kWh/m2. The emission from the traction sector is 12.2 kgCO2/(vehicle‐km) and from the station sector is 118.6 kgCO2/m2. The study also identifies the energy‐intensive lines of the Tianjin Metro and compares the energy utilization among various global metro systems. The authors hope that this study can help shed light on the assessment of the energy status of metro systems and serve as a source of information for other City‐Metros to implement energy‐saving management.

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Potential for metro rail energy savings and emissions reduction via eco-driving

Cited by 25 publications

References 30 publications

Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service

Characterizing Fuel Use and Emission Hotspots for a Diesel-Operated Passenger Rail Service

A Simulation Approach for Optimising Energy-Efficient Driving Speed Profiles in Metro Lines

Characteristics and assessment of the electricity consumption of metro systems: A case study of Tianjin, China

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