Multi-variant-based design space exploration for automotive embedded systems

This paper proposes a novel design method for modern automotive electrical and electronic (E/E) architecture component platforms. The addressed challenge is to derive an optimized component platform termed Baukasten where components, i. e., different manifestations of Electronic Control Units (ECUs), are reused across different car configurations, models, or even OEM companies. The proposed approach derives an efficient graph-based exploration model from defined functional variants. From this, a novel symbolic formulation of multi-variant resource allocation, task binding, and message routing serves as input for a state-of-the-art hybrid optimization technique to derive the individual architecture for each functional variant and the resulting Baukasten at once. For the first time, this enables a concurrent analysis and optimization of individual variants and the Baukasten. Given each manifestation of a component in the Baukasten induces production, storage, and maintenance overhead, we particularly investigate the trade-off between the number of different hardware variants and other established design objectives like monetary cost. We apply the proposed technique to a real-world automotive use case, i. e., a subsystem within the safety domain, to illustrate the advantages of the multi-variant-based design space exploration approach.