Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Energy Optimal Operation of Electric Trains: Development of a Driver Advisory System
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.
2016 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The electric traction system used in trains is the most energy efficient traction system in the transportation sector. Moreover, it has the least NOx and CO2 emissions in comparison to other transportation systems (e.g. busses, passenger cars, airplanes, etc.). On the other hand, they are extremely expensive, mainly due to high installation and maintenance cost of the catenary system, including e.g. overhead lines and substations. Consequently, the share of electrified lines is only slightly higher than non-electrified lines. For instance in Europe, 60% of the railway networks are electrified, and the percentage is much lower in other continents. Battery driven trains are a new generation of electric trains that can overcome such high costs while keeping CO2 emissions and energy consumption low.At the moment, there are only two battery driven electric trains developed and both of the trains are passenger electric multiple units (EMUs). An EMU is an electric train with a traction system in more than one wagon, in contrast to loco-haul electric trains which have a traction system in one wagon only. Energy management during the operation of battery driven trains is a crucial task, as energy optimal operation of trains considering the optimal use of batteries can increase both the operating time and the lifetime of batteries. Energy efficient train operation is realized using driver advisory systems (DAS) that instructs drivers on how to drive trains for minimum energy consumption. The aim of this research is to propose an algorithm for speed profile optimization of both EMUs and battery driven EMUs. The desired algorithm should be suitable as a core component for an online DAS with short response time.Several approaches are proposed in the literature for speed profile optimization of electric trains, and a few of these have been proposed for speed profile optimization of battery driven electric trains. The trains modeled in almost all of the approaches are trains using a notch system for controlling tractive effort. The proposed solution in this research project is to use discrete dynamic programming (DP) to find the optimum speed profile. The application of DP is studied for speed profile optimization of EMUs with a notch system as well as EMUs with a smooth gliding handle for controlling tractive effort. The problem is solved for both normal EMUs and battery driven EMUs.The results of this research show that DP can provide accurate results in a reasonably short time. Moreover, the proposed algorithm can be used as a base for a DAS with fast response time (real-time).

Abstract [sv]

Elektriska traktionssystem i tåg är det mest energieffektiva alternativet inom transportsektorn, och dessutom har det lägst NOx- och CO2-utsläpp i jämförelse med andra transportsystem (exempelvis bussar, personbilar, flygplan, etc.). Å andra sidan är de relativt dyra, främst på grund av höga installations- och underhållskostnader för kontaktledningssystem, inklusive t.ex. luftledningar och transformatorstationer. Följaktligen är andelen elektrifierade linjer något högre än andelen icke-elektrifierade linjer. I Europa är endast 60 % av järnvägsnäten elektrifierade, och andelen är till och med mycket lägre i andra världsdelar. Batteridrivna tåg representerar en ny generation av eltåg som kan nå rimliga kostnader samtidigt med låga CO2-utsläpp och låg energiförbrukning.För närvarande finns det bara två batteridrivna elektriska tåg utvecklade och båda tågen är passagerartåg med elektriska multipla enheter (EMUs). En EMU är ett elektriskt tåg med drivsystem i mer än en vagn, i motsats till lokomotiveltåg som har framdrivningssystemet centrerat till en enda vagn. Energihantering under driften av batteridrivna tåg är en viktig uppgift, och vid en energioptimal drift av tåget tillsammans med en optimerad användning av batterier ökar både driftstiden och livscykeln för batterierna. Energioptimal drift tillämpas i tågdrift med hjälp av ett system som kallas förarrådgivning (eng. Driver Advisory Support, DAS). DAS är ett system som instruerar tågföraren om hur man kör tåget med minimal energiförbrukning.Syftet med denna forskning är att föreslå en algoritm för hastighetsprofilsoptimering av både vanliga EMU:er samt motsvarande batteridrivna. Den önskade algoritmen skall vara lämpad att användas som en bas för ett online-DAS med kort svarstid.Olika metoder föreslås i litteraturen för hastighetsprofilsoptimering av eltåg, och några även för hastighetsprofilsoptimering av batteridrivna elektriska tåg. De tågmodeller som används har oftast ett så kallat “notch”-system för kontrollering av dragkraft. Den föreslagna lösningen i detta forskningsprojekt är att använda diskret dynamisk programmering (DP) för att hitta den optimala hastighetsprofilen. Tillämpning av DP studeras för hastighetsprofilsoptimering av EMU:er både med ”notch”-system samt EMU:er med ett kontinuerligt glidhandtag för styrning av dragkraft. Problemet löses för både normala EMU:er och batteridrivna EMU:er.Resultaten av denna forskning visar att DP kan ge korrekta resultat inom rimlig tid. Vidare kan den föreslagna algoritmen användas som en bas för en DAS med snabb svarstid (realtid).

Place, publisher, year, edition, pages
Västerås: Mälardalen University , 2016.
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 237
National Category
Environmental Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-31494ISBN: 978-91-7485-267-7 (print)OAI: oai:DiVA.org:mdh-31494DiVA: diva2:925586
Presentation
2016-06-14, Paros, Mälardalens högskola, Västerås, 09:00 (English)
Opponent
Supervisors
Projects
STREAM
Funder
VINNOVA
Available from: 2016-05-03 Created: 2016-05-02 Last updated: 2016-05-18Bibliographically approved
List of papers
1. Optimal Control of an EMU Using Dynamic Programming
Open this publication in new window or tab >>Optimal Control of an EMU Using Dynamic Programming
2015 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 75, 1913-1919 p.Article in journal (Refereed) Published
Abstract [en]

A model is developed for minimizing the energy consumption of an electric multiple unit through optimized driving style, based on Hamilton-Jacobi-Bellman equation and Bellman's backward approach. Included are the speed limits, track profile (elevations), different driving modes and the train load. This paper includes aspects like the power loss in the auxiliary systems, time management, validation of the model regarding energy calculations and a study on discretization and the accuracy of the model. The model will be used as a base for a new driver advisory system. 

National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-29330 (URN)10.1016/j.egypro.2015.07.184 (DOI)000361030003026 ()2-s2.0-84947087187 (Scopus ID)
Conference
7th International Conference on Applied Energy (ICAE), MAR 28-31, 2015, Abu Dhabi, U ARAB EMIRATES
Available from: 2015-10-15 Created: 2015-10-15 Last updated: 2017-11-10Bibliographically approved
2. Optimal Control of an EMU Using Dynamic Programming and Tractive Effort as the Control Variable
Open this publication in new window or tab >>Optimal Control of an EMU Using Dynamic Programming and Tractive Effort as the Control Variable
2015 (English)In: Proceedings of the 56th SIMS, Linköping University Electronic Press, Linköpings universitet, 2015, 377-382 p.Conference paper, Published paper (Refereed)
Abstract [en]

Problem of optimal train control with the aim of minimizing energy consumption is one of the old optimal control problems. During last decades different solutions have been suggested based on different optimization techniques, each including a certain number of constraints or different train configurations, one being the control on the tractive effort available from traction motor. The problem is previously solved using dynamic programming for trains with continuous tractive effort, in which velocity was assumed to be the control variable. The paper at hand presents a solution based on dynamic programming for solving the problem for trains with discrete tractive effort. In this approach, tractive effort is assumed to be the control variable. Moreover a short comparison is made between two approaches regarding accuracy and ease of application in a driver advisory system.

Place, publisher, year, edition, pages
Linköping University Electronic Press, Linköpings universitet: , 2015
Keyword
Optimal Control; Dynamic Programming; Electric Trains
National Category
Energy Systems Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-29921 (URN)10.3384/ecp15119377 (DOI)978-91-7685-900-1 (ISBN)
Conference
The 56th Conference on Simulation and Modelling (SIMS 56), October 07-09, 2015, Linköping, Sweden
Funder
VINNOVA, 2014-04319
Available from: 2015-12-13 Created: 2015-12-13 Last updated: 2017-03-22Bibliographically approved
3. Flow batteries use potential in heavy vehicles
Open this publication in new window or tab >>Flow batteries use potential in heavy vehicles
2015 (English)In: Electrical Systems for Aircraft, Railway and Ship Propulsion, ESARS, 2015, Article number 7101496- p.Conference paper, Published paper (Refereed)
Abstract [en]

Although batteries have been used in personal vehicles for more than a hundred years, the cost of the technology, limitation in range, absence of sufficient recharging infrastructure and rapid development of internal combustion engines during the mid-twentieth century limited its use to very niche applications. More recently, a global need for reducing CO2 emissions from fossil fuel usage and the great developments in power systems as well as in battery technology offers electric vehicles the possibility to return to the market, not just for personal use but also for a wide variety of transportation applications. In the present paper, a feasibility study for using flow batteries in heavy vehicles, more specifically, construction equipment is presented. The authors used measured energy demand profiles for different operation conditions of a wheel loader and developed a simulation model for a vanadium redox flow battery to test the performance of this vehicle using a flow battery. Additionally, the authors did a short theoretical analysis for the potential for flow batteries in train transportation, focusing on the requirements and limitations of the technology for this application.

National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-31547 (URN)10.1109/ESARS.2015.7101496 (DOI)2-s2.0-84946204604 (Scopus ID)9781479974009 (ISBN)
Conference
International Conference on Electrical Systems for Aircraft, Railway, Ship Propulsion and Road Vehicles, ESARS 2015; Aachen; Germany; 3 March 2015 through 5 March 2015
Available from: 2016-05-11 Created: 2016-05-11 Last updated: 2017-03-22Bibliographically approved
4. Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort
Open this publication in new window or tab >>Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort
2016 (English)In: 2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Electric traction system is the most energy efficient traction system in railways. Nevertheless, not all railway networks are electrified, which is due to high maintenance and setup cost of overhead lines. One solution to the problem is battery-driven trains, which can make the best use of the electric traction system while avoiding the high costs of the catenary system. Due to the high power consumption of electric trains, energy management of battery trains are crucial in order to get the best use of batteries. This paper suggests a general algorithm for speed profile optimization of an electric train with an on-board energy storage device, during catenary-free operation on a given line section. The approach is based on discrete dynamic programming, where the train model and the objective function are based on equations of motion rather than electrical equations. This makes the model compatible with all sorts of energy storage devices. Unlike previous approaches which consider trains with throttle levels for tractive effort, the new approach considers trains in which there are no throttles and tractive effort is controlled with a controller (smooth gliding handle with no discrete levels). Furthermore, unlike previous approaches, the control variable is the velocity change instead of the applied tractive effort. The accuracy and performance of the discretized approach is evaluated in comparison to the formal movement equations in a simulated experimented using train data from the Bombardier Electrostar series and track data from the UK.

Keyword
Digital storage; Dynamic programming; Electric batteries; Electric traction; Electric vehicles; Energy efficiency; Energy storage; Equations of motion; Overhead lines; Power electronics; Railroads Catenary free operation; Electric traction system; Electric trains; Electrical equations; High power consumption; Objective functions; On-board energy storage; Speed profile
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:mdh:diva-31549 (URN)10.1109/SPEEDAM.2016.7525913 (DOI)000387110600104 ()2-s2.0-84994182006 (Scopus ID)
Conference
2016 International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM 2016; Capri; Italy; 22 June 2016 through 24 June 2016; Category numberCFP1648A-ART; Code 123134
Available from: 2016-05-11 Created: 2016-05-11 Last updated: 2017-03-22Bibliographically approved

Open Access in DiVA

fulltext(608 kB)278 downloads
File information
File name FULLTEXT02.pdfFile size 608 kBChecksum SHA-512
4a818482c07ee334eafecc2afd94b4754b8fcaad06d7a056c11848d297dbd62b7bbf5a53e2628b9fa84d49132bf0eab077c0592940a8163609149a45fc270989
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Ghaviha, Nima
By organisation
Future Energy Center
Environmental Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 278 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 785 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf