Overview
The complexity of software-defined vehicles (SDVs) brings challenges in maintaining safety and optimizing performance. The adoption of new service-oriented architectures for software and new Electrical and Electronics (E/E) hardware architecture, along with Advanced Driver Assistance Systems (ADAS), Autonomous Driving (AD), has increased safety system complexity, including cybersecurity risks due to over-the-air (OTA) updates.
Achieving effective integration between software and hardware is crucial, with Model-Based Systems Engineering (MBSE) offering an efficient way to manage these demands. By employing digital models to guide requirements, architecture, design, and validation, this practice promotes early detection of problems, ensures adherence to regulations, and expedites the development process.
When using multidisciplinary and multifidelity analyses, engineers can perform precise trade-off studies, enabling balanced decisions during the concept design phase. Additionally, integrating advanced system simulations and reduced-order models enhances validation and verification processes, ensuring alignment with safety, performance, and regulatory requirements.