Monitoring and Diagnosing Software-Defined Vehicle Architectures DSA Daten- und Systemtechnik Aachen GmbH

Format:

Book

Conference/Event

Author/Creator:

Böhlen, Boris, author.

Contributor:

Fischer, Diana

Conference Name:

Symposium on International Automotive Technology (2026) (2026-01-28 : Pune, India)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2026

Summary:

Software-Defined Vehicles (SDV) are fostered through initiatives like SOAFEE and Eclipse SDV promoting the use of cloud-native approaches, distributed workloads and service-oriented architectures (SOA). This means that in these systems each vehicle is connected to the cloud and functions are executed both inside the vehicle and in the cloud. So far, there are no established solutions for monitoring and diagnosing SDVs. In designing these solutions, the cost-sensitive nature of every component inside a vehicle must be considered since it makes it unlikely that significant resources will be provided just for diagnostics. Therefore, conventional data centre monitoring approaches that usually rely on transferring large amounts of data to dedicated servers are not directly applicable in this scenario. To illustrate the challenges in providing new solutions for diagnosing and monitoring SDVs, a SOA that has been defined and studied in research projects is introduced. In this architecture, every vehicle function is implemented by an independent service while an orchestrator manages them. The ASAM SOVD (ISO 17978) standard was introduced as a successor for existing diagnostic protocols such as UDS specifically to support diagnosing SDVs. Though it already goes beyond UDS in functionality and supports diagnosing more complex issues, e.g. by allowing to access log files, it does not yet provide functionality specifically related to diagnosing problems that can arise in an SOA. This would require functionality such as validating service quality, chain-of-effects, or dynamic resource usage. Additionally, as services can be distributed between the vehicle and the cloud, diagnostic functions must take that into account. By transferring established IT solutions for monitoring and diagnostics to vehicles and extending the SOVD standard, the paper proposes a solution that fills current gaps: on-board monitoring of services including their chain-of-effects, fault generation for erroneous conditions, analysis of historical data, et cetera With SOVD progressing toward ISO standardisation, its adoption extends beyond automotive passenger vehicles into industries such as off-highway and agricultural machinery, which are also introducing Automotive Ethernet and HPC architectures. These developments not only influence diagnostic architectures in SDVs but also have strategic implications for production processes and aftersales service models, as discussed in the concluding section

Notes:

Vendor supplied data

Publisher Number:

2026-26-0677

Access Restriction:

Restricted for use by site license