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A driver advisory system with dynamic losses for passenger electric multiple units
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0001-8697-855x
RISE SICS, Västerås, Sweden.
Bombardier Transportation, Västerås, Swede.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center.ORCID iD: 0000-0002-7233-6916
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2017 (English)In: Transportation Research Part C: Emerging Technologies, ISSN 0968-090X, E-ISSN 1879-2359, Vol. 85, p. 111-130Article in journal (Refereed) Published
Abstract [en]

Driver advisory systems, instructing the driver how to control the train in an energy efficient manner, is one the main tools for minimizing energy consumption in the railway sector. There are many driver advisory systems already available in the market, together with significant literature on the mathematical formulation of the problem. However, much less is published on the development of such mathematical formulations, their implementation in real systems, and on the empirical data from their deployment. Moreover, nearly all the designed driver advisory systems are designed as an additional hardware to be added in drivers’ cabin. This paper discusses the design of a mathematical formulation and optimization approach for such a system, together with its implementation into an Android-based prototype, the results from on-board practical experiments, and experiences from the implementation. The system is based on a more realistic train model where energy calculations take into account dynamic losses in different components of the propulsion system, contrary to previous approaches. The experimental evaluation shows a significant increase in accuracy, as compared to a previous approach. Tests on a double-track section of the Mälaren line in Sweden demonstrates a significant potential for energy saving.

Place, publisher, year, edition, pages
Elsevier Ltd , 2017. Vol. 85, p. 111-130
Keywords [en]
Driver advisory system, Electric multiple unit, Energy efficiency, Driver training, Electric losses, Electric railroads, Electric traction, Energy conservation, Energy utilization, Propulsion, Railroad transportation, Rapid transit, Advisory systems, Double-track section, Energy calculation, Experimental evaluation, Mathematical formulation, Minimizing energy, Optimization approach, control system, electric vehicle, energy use, optimization, railway transport, train, Sweden
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-37410DOI: 10.1016/j.trc.2017.09.010ISI: 000423006600006Scopus ID: 2-s2.0-85034098198OAI: oai:DiVA.org:mdh-37410DiVA, id: diva2:1163620
Available from: 2017-12-07 Created: 2017-12-07 Last updated: 2018-02-08Bibliographically approved

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Ghaviha, NimaDahlquist, Erik

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