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One of the many challenges facing electronic 1 system architects is how to provide a cost estimate related to design decisions over the entire life-cycle and product line of the architecture. Various cost modeling techniques may be used to perform this estimation. However, the estimation is often done in an ad-hoc manner, based on specific design scenarios or business assumptions. This situation may yield an unfair comparison of architectural alternatives due to the limited scope of the evaluation. A preferred estimation method would involve rigorous cost modeling based on architectural design cost drivers similar to those used in the manufacturing (e.g. process-based technical cost modeling) or in the enterprise software domain (e.g. COCOMO). This paper describes an initial study of a cost model associated with automotive electronic system architecture.

The increasing role of electronics in automotive systems drives the design of fault tolerant architectures. We envision that tool-based automated analysis of such applications will be increasingly necessary for system designers. In this work, we describe a tool flow to support design space exploration of fault tolerant automotive architectures. Within the flow, we describe and apply a self-designed tool that automatically generates a fault tree from a model of an industrial-sized, safety critical automotive control application. The model represents a deployment containing a set of functions that are mapped to a given set of architecture components. The functions implement data acquisition from sensor devices, perform fault management tasks, compute a control law, and issue commands to the actuators. The architecture component abstractions and modeling artifacts include a set of communication links and electronic control units (ECUs) that are distributed throughout the vehicle.

Automotive control applications are implemented over distributed platforms consisting of a number of electronic control units (ECUs) connected by communication buses. During system development, the designer can explore a number of design alternatives: for example, software distribution, software architecture, hardware architecture, and network configuration. Exploring design alternatives efficiently and evaluating them to optimize metrics such as cost, time, resource utilization, and reliability provides an important competitive advantage to OEMs and helps minimize integration risks. We present a methodology (Platform-Based Design) and a framework (Metropolis) to support efficient architecture exploration. We have exercised the methodology and the capabilities of Metropolis for developing a library of automotive architecture components and performed design space exploration on a chassis control sub-system.