Dynamic Switching Speed Reconfiguration for Engine Performance optimization

Today's automotive engine control systems adopt several control strategies that come with tradeoffs between computational load and performance. The current practice is that the switching speeds at which the engine control system changes control strategy is fixed offline, typically based on the average driving need in a standard driving cycle (i.e., vehicle speed profile over time). This is clearly suboptimal since it fails to capture the variation in the driving cycle, and the actual driving cycle may be considerably different from the standard one. In this paper, we propose to dynamically adjust switching speeds based on the predicted driving cycle. We develop a hybrid set of schedulability analysis techniques to tame the complexity of ensuring the real-time schedulability of engine control tasks. We design an effective and efficient optimization algorithm that provides close-to-optimal solutions. Experimental results demonstrate that our approach efficiently finds dynamic switching speeds that significantly improve engine performance over static ones.