Master data

Title: Model-Based Generation of Software Configurations in Mechatronic Systems
Subtitle:
Abstract:

An essential part of the mechatronic system is the software, which is responsible to bring functionality into the system consisting of mechanical, electronic and electrical parts. The software must be tailored to the specific hardware to fulfill tasks (e.g. control, monitoring) according to the system requirements. In today‘s industrial practice, the design is mainly done manually. First the entire architecture is drawn using drawing tools. Based on this software developers derive the low-level specification using their low-level development environments. This is error prone and time-consuming due to the fact, that a large number of hardware parameters have to be taken in account and the informal specification does not allow to derive these parameters. To improve this we present here an approach where the overall architecture of the mechatronic system is described using a Domain-Specific Conceptual Modeling Language (DSML) using the example of Electric Vehicle Testbeds. Based on this model the low-level software configurations are generated rule-based. In this paper we present the concepts of the DSML, explain the transformation rules and show the functionality of the generator by introducing a practical example.

Keywords: Modeling; Metamodel; DSML; Software; Generator; Transformation; Configuration
Publication type: Article in Proceedings (Authorship)
Publication date: 05.05.2020 (Print)
Published by: 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)

H. Mayr, S. Rinderle-Ma, S. Strecker
Gesellschaft für Informatik e.V.

to publication
 ( Gesellschaft für Informatik e.V.; H. Mayr, S. Rinderle-Ma, S. Strecker )
Title of the series: Lecture Notes in Informatics
Volume number: P-302
First publication: Yes
Page: pp. 29 - 44

Versionen

Keine Version vorhanden
Publication date: 05.05.2020
ISBN:
  • 978-3-88579-698-5
ISSN: 1617-5468
Homepage: https://dl.gi.de/handle/20.500.12116/31845

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Categorisation

Subject areas
  • 102 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: n.a.)
Classification raster of the assigned organisational units:
working groups
  • Application Engineering

Cooperations

Organisation Address
AVL List GmbH
Hans-List-Pl. 1
8010 Graz
Austria - Styria
Hans-List-Pl. 1
AT - 8010  Graz

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