Automatic Model Based Partitioning of Distributed Automotive Electric Systems 2004-01-0706
There are a number of tools available to assist the engineer during the automotive electronics design process, for example when transferring a graphical specification to a real time rapid prototyping environment. One step in this tool chain however is largely ignored by automated design tools: mapping a large monolithic model to a distributed system, more specifically the mapping of several functions on only a few electronic control units (ECUs) which are connected by a bus. In this paper we will present a method to analyze the underlying functional structure of a given model, partition it using a heuristic algorithm and verify the results with a model of the CAN bus.
Based on a given functional model, we will show how to extract an algebraic representation of the communication behavior, the adjacency matrix. Using the adjacency matrix, the heuristic algorithm Best Gain First can be applied to map functions to ECUs. A cost function is used to optimize the bus load while still meeting constraints such as maximum processor load. A special focus has been put on this cost function because it has proven to be an effective way to improve the performance of the system.
The results of the partitioning process have been verified using a message-based model of the CAN bus, which allows for detailed observation and evaluation, both off- and online. Overall we will show in this paper that it is possible to significantly reduce the bus load of a distributed system by using a heuristic partitioning algorithm.