Publikation: Model-based Testbed Design for Electric...
Stammdaten
Titel: | Model-based Testbed Design for Electric Vehicles |
Untertitel: | |
Kurzfassung: | 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. |
Schlagworte: | Modeling, Meta-Model, Ontology, Circuit plan, Testbed, MDA, DSML, Electric Vehicle |
Publikationstyp: | Beitrag in Proceedings (Autorenschaft) |
Erscheinungsdatum: | 05.05.2020 (Print) |
Erschienen in: |
40 Years EMISA - Digital Ecosystems of the Future: Methodology, Techniques and Applications. Proc. 40th Conf. of the GI SIG EMISA
40 Years EMISA - Digital Ecosystems of the Future: Methodology, Techniques and Applications. Proc. 40th Conf. of the GI SIG EMISA
(2020)
(
Gesellschaft für Informatik e.V.;
H. Mayr, S. Rinderle-Ma, S. Strecker
)
H. Mayr, S. Rinderle-Ma, S. Strecker
|
Titel der Serie: | Lecture Notes in Informatics |
Bandnummer: | P-304 |
Erstveröffentlichung: | Ja |
Seite: | S. 45 - 58 |
Versionen
Keine Version vorhanden |
Erscheinungsdatum: | 05.05.2020 |
ISBN: |
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ISSN: | 1617-5468 |
Homepage: | https://dl.gi.de/handle/20.500.12116/33138?locale-attribute=en |
AutorInnen
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Fakultät für Technische Wissenschaften
Institut für Artificial Intelligence und Cybersecurity
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AT - A-9020 Klagenfurt |
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AVL List GmbH
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AT - 8010 Graz |
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