Development and control of a rail vehicle model to reduce energy consumption and carbon dioxide emissions

Harrison, Tim J.; Midgley, Will; Goodall, Roger M.; Ward, Christopher P.

doi:10.1177/0954409721993632

Cited by 12 publications

(20 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The work reported here extends and improves upon the model initially described in [17]. An overview of this model is given in Fig.…”

Section: Rail Vehicle Modelmentioning

confidence: 67%

“…where P em is the motor electrical power, P aux is the auxiliary power use, n m ¼ 12 is the total number of motors, V i is the motor input voltage, and i m is the single motor current. The traction motor is modelled as a DC motor as given in [17].…”

Section: Co 2 Emissions 31 Model Resultsmentioning

confidence: 99%

“…1 Components of the train model. OLE-overhead line equipment [17] An investigation into intermittent electrification strategies and an analysis of resulting……”

Section: Train Dynamics and Propertiesmentioning

confidence: 99%

“…The diesel engine model used in this simulation was based on a model of a heavy goods vehicle [25] scaled to match the specifications of the class 80x train engines [26]. More information on the dynamics of the engine/generator set is available in [17].…”

Section: Diesel Engine and Generatormentioning

confidence: 99%

“…The model gave fuel consumption of 3.27-3.46 L/mile and 0.016-0.017 L/(passengerÁkm)-in line with similar rolling stock such as the Class 221 and Class 180. Further details of the validation are given in [17].…”

Section: Model Validationmentioning

confidence: 99%

See 4 more Smart Citations

An investigation into intermittent electrification strategies and an analysis of resulting CO2 emissions using a high-fidelity train model

et al. 2021

Self Cite

View full text Add to dashboard Cite

A near-term strategy to reduce emissions from rail vehicles, as a path to full electrification for maximal decarbonisation, is to partially electrify a route, with the remainder of the route requiring an additional self-powered traction option. These rail vehicles are usually powered by a diesel engine when not operating on electrified track and are referred to as bi-mode vehicles. This paper analyses the benefits of discontinuous electrification compared to continuous electrification using the CO2 estimates from a validated high-fidelity bi-mode (diesel-electric) rail vehicle model. This analysis shows that 50% discontinuous electrification provides a maximum of 54% reduction in operational CO2 emissions when compared to the same length of continuously electrified track. The highest emissions savings occurred when leaving train stations where vehicles must accelerate quickly to line speed. These results were used to develop a linear regression model for fast estimation of CO2 emissions from diesel running and electrification benefits. This model was able to estimate the CO2 emissions from a route to within 10% of that given by the high-fidelity model. Finally, additional considerations such as cost and the embodied CO2 in electrification infrastructure were analysed to provide a comparison between continuous and discontinuous electrification. Discontinuous electrification can cost up to 56% less per reduction in lifetime emissions than continuous electrification and can save up to 2.3 times more lifetime CO2 per distance electrified.

show abstract

“…The work reported here extends and improves upon the model initially described in [17]. An overview of this model is given in Fig.…”

Section: Rail Vehicle Modelmentioning

confidence: 67%

Section: Co 2 Emissions 31 Model Resultsmentioning

confidence: 99%

“…1 Components of the train model. OLE-overhead line equipment [17] An investigation into intermittent electrification strategies and an analysis of resulting……”

Section: Train Dynamics and Propertiesmentioning

confidence: 99%

Section: Diesel Engine and Generatormentioning

confidence: 99%

Section: Model Validationmentioning

confidence: 99%

See 3 more Smart Citations