timing and schedulability analysis for distributed automotive control applications
High-end cars today consist of more than 100 electronic control units (ECUs) that are connected to a set of sensors and actuators and run multiple distributed control applications. The design flow of such architectures consists of specifying control applications as Simulink/Stateflow models, followed by generating code from them and finally mapping such code onto multiple ECUs. In addition, the scheduling policies and parameters on both the ECUs and the communication buses over which they communicate also need to be specified. These policies and parameters are computed from high-level timing and control performance constraints. The proposed tutorial will cover different aspects of this design flow, with a focus on timing and schedulability problems. After reviewing the basic concepts of worst-case execution time analysis and schedulability analysis, we will discuss the differences between meeting timing constraints (as in classical real-time systems) and meeting control performance constraints (e.g., stability, steady and transient state performance). We will then describe various control performance related schedulability analysis techniques and how they may be tied to model-based software development. Finally, we will discuss various schedule synthesis techniques, both for ECUs as well as for communication protocols like FlexRay, so that control performance constraints specified at the model-level may be satisfied. Throughout the tutorial different commercial as well as academic tools will be discussed and demonstrated.
schedulability analysis control applications timing analysis distributed automotive systems