Development and Experimental Validation of an Adaptive, Piston-Damage-Based Combustion Control System for SI Engines: Part 2—Implementation of Adaptive Strategies

Alessandro Brusa, Nicolò Cavina, Nahuel Rojo, Jacopo Mecagni, Enrico Corti, Davide Moro, Matteo Cucchi and Nicola Silvestri
Additional contact information
Alessandro Brusa: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Nicolò Cavina: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Nahuel Rojo: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Jacopo Mecagni: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Enrico Corti: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Davide Moro: Department of Industrial Engineering, School of Engineering and Architecture, University of Bologna, 40126 Bologna, Italy
Matteo Cucchi: Ferrari S.p.A., 41053 Maranello MO, Italy
Nicola Silvestri: Ferrari S.p.A., 41053 Maranello MO, Italy

Energies, 2021, vol. 14, issue 17, 1-21

Abstract: 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.

Keywords: knock; combustion; efficiency improvement; CO 2 emissions; control; adaptive strategy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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