This work is focused on the development and validation of a spark advance controller, based on a piston “damage” model and a predictive knock model. The algorithm represents an integrated and innovative way to manage both the knock intensity and combustion phase. It is characterized by a model-based open-loop algorithm with the capability of calculating with high accuracy the spark timing that achieves the desired piston damage in a certain period, for knock-limited engine operating conditions. Otherwise, it targets the maximum efficiency combustion phase. Such controller is primarily thought to be utilized under conditions in which feedback is not needed. In this paper, the main models and the structure of the open-loop controller are described and validated. The controller is implemented in a rapid control prototyping device and validated reproducing real driving maneuvers at the engine test bench. Results of the online validation process are presented at the end of the paper.

This work focuses on the implementation of innovative adaptive strategies and a closed-loop chain in a piston-damage-based combustion controller. In the previous paper (Part 1), implemented models and the open loop algorithm are described and validated by reproducing some vehicle maneuvers at the engine test cell. Such controller is further improved by implementing self-learning algorithms based on the analytical formulations of knock and the combustion model, to update the fuel Research Octane Number (RON) and the relationship between the combustion phase and the spark timing in real-time. These strategies are based on the availability of an on-board indicating system for the estimation of both the knock intensity and the combustion phase index. The equations used to develop the adaptive strategies are described in detail. A closed-loop chain is then added, and the complete controller is finally implemented in a Rapid Control Prototyping (RCP) device. The controller is validated with specific tests defined to verify the robustness and the accuracy of the adaptive strategies. Results of the online validation process are presented in the last part of the paper and the accuracy of the complete controller is finally demonstrated. Indeed, error between the cyclic and the target combustion phase index is within the range ±0.5 Crank Angle degrees (°CA), while the error between the measured and the calculated maximum in-cylinder pressure is included in the range ±5 bar, even when fuel RON or spark advance map is changing.