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Speed Profile Optimization of Catenary-free Electric Trains with Lithium-ion Batteries
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Mälardalen University.ORCID iD: 0000-0001-8697-855x
Research Institutes of Sweden RISE SICS Västerås.ORCID iD: 0000-0003-1597-6738
Bombardier Transportation.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-7233-6916
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Catenary-free operated electric trains, as one of the recent technologies in railwaytransportation, has opened a new field of research: speed profile optimization and energy optimaloperation of catenary-free operated electric trains. A well-formulated solution for this problem shouldconsider the characteristics of the energy storage device using a validated model and method. This paper,discusses the consideration of the battery behavior in the problem of speed profile optimization ofcatenary-free operated electric trains. We combine the single mass point train model with an electricalbattery model and apply a dynamic programming approach to minimize the charge taken from thebattery during the catenary-free operation. The models and the method are validated and evaluatedagainst experimental data gathered from the test runs of an actual battery driven train tested in Essex,UK. The results show a significant potential in energy saving. Moreover, we show that the optimumspeed profiles generated using our approach consume less charge from the battery compared to theprevious approaches.

Keywords [en]
Electric Trains, Catenary-free Operation, Speed Profile Optimization, Energy Efficiency
National Category
Energy Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-41132OAI: oai:DiVA.org:mdh-41132DiVA, id: diva2:1253456
Funder
VINNOVA, 2014-04319VINNOVA, 2012-01277Available from: 2018-10-04 Created: 2018-10-04 Last updated: 2018-10-15Bibliographically approved
In thesis
1. Increasing Energy Efficiency in Electric Trains Operation: Driver Advisory Systems and Energy Storage
Open this publication in new window or tab >>Increasing Energy Efficiency in Electric Trains Operation: Driver Advisory Systems and Energy Storage
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Electric traction is the most efficient traction system in the railway transportation. However, due to the expensive infrastructure and high power demand from the grid, the share of electric trains in the railway transportation is still lower than other trains. Two of the possible solutions to increase the share of electric trains are: optimal train operation to minimize energy consumption, the use of batteries as the energy source for driving electric trains on non-electrified lines. This thesis aims to extend the knowledge in the field of energy optimal operation of electric trains and battery-driven electric trains.

Energy optimal operation of electric trains is supervised using a driver advisory system (DAS), which instructs the driver to operate the train in an energy-efficient manner. This thesis contributes to DAS technology under two topics: the increase of energy efficiency and the design of DAS.

This thesis presents a complete procedure of designing a DAS from the mathematical formulation to application on the train. The designed DAS is in the form of an Android application and is based on a dynamic programming approach. The computational performance of the approach is enhanced using heuristic state reducing rules based on the physical constraints of the system. The application of the DAS shows a potential reduction of 28% in energy consumption.

This thesis considers the detailed energy losses in the whole propulsion system using a regression model that is generated from validated physical models. The application of the regression model instead of a previous constant efficiency factor model results in 2.3% reduction in energy consumption of the optimum speed profiles.

Based on the solution for the normal electric trains, a solution is also offered for the optimal operation of battery-driven electric trains, in which the characteristics of the battery as one of the main components are considered using an electrical model. The solution presented in this thesis, is to combine the popular single mass point train model with an electrical circuit battery model.

Furthermore, this thesis evaluates the performance of the optimization approaches and validates the models against the measurements from actual drives of a real-life battery train. The results show a potential of around 30% reduction in the charge consumption of the battery.

The results of this thesis (algorithms and the Android application) are provided as open source for further research in the field of energy efficient train control.

Place, publisher, year, edition, pages
Västerås: Mälardalen University, 2018
Series
Mälardalen University Press Dissertations, ISSN 1651-4238 ; 275
Keywords
Driver Advisory System, Catenary-free Operation, Electric Train, Electric Multiple Unit, Battery, Energy Efficiency, Energy Storage, Speed Profile Optimization
National Category
Energy Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-41136 (URN)978-91-7485-409-1 (ISBN)
Public defence
2018-11-16, Pi, Mälardalens högskola, Västerås, 13:00 (English)
Opponent
Supervisors
Projects
STREAM
Funder
VINNOVA, 2014-04319VINNOVA, 2012-01277
Available from: 2018-10-08 Created: 2018-10-06 Last updated: 2018-10-16Bibliographically approved

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Ghaviha, NimaDahlquist, Erik

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