Challenges of Next-Generation Electronic Architectures in the SDV Era
Software has become the key to innovation and is transforming entire industries. If Software-Defined Vehicles (SDV) open up a wealth of possibilities in terms of innovation, customization and differentiation, they also pose intricate challenges to E/E architectures:
Demand for more safety-critical and compute-intensive functions such as ADAS and ultimately autonomous driving,
High-performance and timing-predictable networking solutions to cope with the dramatic increase in bandwidth demand created by increasing number of bandwidth-demanding sensors such as cameras,
Consolidation of today’s numerous “domain ECU’s” into a small number of high-performance multi-domain integration platforms with redundancy requirements,
Over-the-Air (OTA) updates and vehicle-to-cloud real-time communication,
Predictability of highly-complex execution platforms comprising one or several different OSes, possibly a hypervisor, a service-oriented middleware, running on SoCs with heterogeneous cores – see this study by Volvo Cars and Cognifyer.
Speed-up Design Exploration, Optimization and Validation of Next-Generation SDVs with RTaW-Pegase/SDV Platform
System Level Modelling, Configuration and Design-Space Exploration
Unified Modeling and Simulation for Networks and Software in a Single Platform
DDS- and SOME/IP-based Service Oriented Architectures
RTaW and RTI have partnered to provide DDS & TSN solutions for mission-critical systems.
Compare design options - here, effect on loads & latencies of periodic activations vs event-triggered activations
“The competition in the smart electric vehicle (EV) market necessitates the swift introduction of new features. This, in turn, demands a new generation of EEA (Electrical and Electronic Architecture) and communication technologies. The implementation of a brand-new tech stack results in challenges when addressing communication and task scheduling problems. RTaW’s SDV functionality enables us to model the temporal behavior of the vehicle and conduct insightful analysis of each activity chain. Throughout this process, the tool provides various scheduling models, state-of-the-art simulation algorithms, and, with RTaW’s robust support, assists us in identifying the traffic and CPU peaks of the system. Ultimately, it helps us pinpoint the appropriate solution. RTaW-Pegase plays a crucial role as a key tool in the development of next-generation EEA.”