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Modelling centralised automotive E/E software architectures
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-8027-0611
Gran Sasso Science Institute (GSSI), L'Aquila, Italy.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3242-6113
2024 (English)In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 59, article id 102289Article in journal (Refereed) Published
Abstract [en]

The automotive domain is living in an exciting period triggered by challenging business and technology drivers, like electrification, autonomous driving, over-the-air software updates and connected vehicles, just to mention a few. This profoundly impacted the electric and electronic automotive architecture and pushed more and more manufacturers to shift towards more centralised electric and electronic architectures for their future automotive software systems. In fact, future centralised architectures are considered to be pivotal to meeting the above-mentioned market needs, as well as evolving customer requirements. In this work, we first analyse the readiness of four main automotive architectural languages to represent novel vehicle-centralised architectures. Based on the analysis results, we propose an extension to one of these languages to fully support the modelling of technical reference architectures for centralised vehicles. We validate the proposed extension using workshops with experts in the automotive domain and using an automotive use case describing an autonomous quarry.

Place, publisher, year, edition, pages
Elsevier Ltd , 2024. Vol. 59, article id 102289
Keywords [en]
Architectural languages, Automotive software architectures, Centralised architectures, Electric and Electronic (E/E) architecture, Modeling languages, Vehicles, Automotive domains, Automotive software, Automotive software architecture, Automotives, Business drivers, Centralised, Centralized architecture, Electric and electronic architectures, Technology drivers, Software architecture
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-65144DOI: 10.1016/j.aei.2023.102289ISI: 001140064100001Scopus ID: 2-s2.0-85179583938OAI: oai:DiVA.org:mdh-65144DiVA, id: diva2:1821892
Available from: 2023-12-21 Created: 2023-12-21 Last updated: 2024-01-31Bibliographically approved

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Bucaioni, AlessioMubeen, Saad

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