Model-based design of resource-efficient automotive control software

Automotive platforms today run hundreds of millions of lines of software code implementing a large number of different control applications spanning across safety-critical functionality to driver assistance and comfort-related functions. While such control software today is largely designed following model-based approaches, the underlying models do not take into account the details of the implementation platforms, on which the software would eventually run. Following the state-of-the-art in control theory, the focus in such design is restricted to ensuring the stability of the designed controllers and meeting control performance objectives, such as settling time or peak overshoot. However, automotive platforms are highly cost-sensitive and the issue of designing "resource-efficient" controllers has largely been ignored so far and is addressed using very ad hoc techniques. In this paper, we will illustrate how, following traditional embedded systems design oriented thinking, computation, communication and memory issues can be incorporated in the controller design stage, thereby resulting in control software not only satisfying the usual control performance metrics but also making efficient utilization of the resources on distributed automotive architectures.