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Optimal Control of a Battery Train Using Dynamic Programming
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-8697-855X
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-1597-6738
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-7233-6916
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0003-4589-7045
2015 (English)Conference paper, Presentation (Other academic)
Abstract [en]

Electric propulsion system in trains has the highest efficiency compared to other propulsion systems (i.e. steam and diesel). Still, electric trains are not used on all the routes, due to the high setup and maintenance cost of the catenary system. Energy storage technologies and the battery driven trains however, make it possible to have the electric trains on the non-electrified routes as well. High energy consumption of the electric trains, makes the energy management of such trains crucial to get the best use of the energy storage device. This paper suggests an algorithm for the optimal control of the catenary free operation of an electric train equipped with an onboard energy storage device. The algorithm is based on the discrete dynamic programming and Bellman’s backward approach. The objective function is to minimize the energy consumption, i.e. having the maximum battery level left at the end of the trip. The constraints are the trip time, battery capacity, local speed limits and limitations on the traction motor. Time is the independent variable and distance, velocity and battery level are the state variables. All of the four variables are discretized which results in some inaccuracy in the calculations, which is discussed in the paper. The train model and the algorithm are based on the equations of motion which makes the model adjustable for all sorts of electric trains and energy storage devices. Moreover, any type of electrical constraints such as the ones regarding the voltage output of the energy storage device or the power output can be enforced easily, due to the nature of the dynamic programming. 

Place, publisher, year, edition, pages
2015.
Keyword [en]
Optimal Control, Dynamic Programming, Energy Storage Device, Electric Trains
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering Energy Systems
Research subject
Energy- and Environmental Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-29922OAI: oai:DiVA.org:mdh-29922DiVA: diva2:882039
Conference
International Conference on Operation Research (OR2015), University of Vienna, 1-4 Sept 2015, Austria
Funder
VINNOVA
Available from: 2015-12-13 Created: 2015-12-13 Last updated: 2017-03-22Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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