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Model-based Testbed Design for Electric Vehicles

Autor(en):
Paczona, Martin [DBLP] ;
Mayr, Heinrich C. [DBLP] ;
Prochart, Guenter [DBLP]
Zusammenfassung
Electric cars boom. This puts pressure on providing and improving tools and systems for electric car development. Electric vehicle testbeds (EVTs) are such systems: they serve for testing all high voltage vehicle components like batteries, inverters or complete engines and help to reduce the need of cost intensive road tests. EVT users like manufacturers of automobiles, aircrafts or train engines mostly have individual requirements. EVTs are therefore typically tailor-made solutions. Today’s approach to customized testbed (component) design starts with drawing the overall architecture using tools like MS Visio; based here-on, software developers, circuit plan designers, and engineers use their specific low-level design and development environments, obviously with no transformation or generation out of the initial drawing with causes all known challenges of such procedure. This paper presents a novel, innovative and scalable approach to EVT design based on an ontology grounded Domain Specific Modeling Language (DSML). It enables the user to describe the customer requirements in the familiar form. The resulting model can then be used to generate circuit diagrams and software configurations. Such approach not only may reduce development time and cost but may increase the quality of the resulting EVT.
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Paczona, M., Mayr, H. C. & Prochart, G., (2020). Model-based Testbed Design for Electric Vehicles. In: Mayr, H. C., Rinderle-Ma, S. & Strecker, S. (Hrsg.), 40 Years EMISA 2019. Bonn: Gesellschaft für Informatik e.V.. (S. 45-58).
@inproceedings{mci/Paczona2020,
author = {Paczona, Martin AND Mayr, Heinrich C. AND Prochart, Guenter},
title = {Model-based Testbed Design for Electric Vehicles},
booktitle = {40 Years EMISA 2019},
year = {2020},
editor = {Mayr, Heinrich C. AND Rinderle-Ma, Stefanie AND Strecker, Stefan} ,
pages = { 45-58 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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Mehr Information

ISBN: 978-3-88579-698-5
ISSN: 1617-5468
Datum: 2020
Sprache: en (en)
Typ: Text/Conference Paper

Keywords

  • Modeling
  • Meta-Model
  • Ontology
  • Circuit plan
  • Testbed
  • MDA
  • DSML
  • Electric vehicle
Sammlungen
  • P304 - 40 Years EMISA 2019 [25]

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Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.