The research objective of this Grant Opportunity for Academic Liaison with Industry (GOALI) Collaborative Research project is to develop accurate yet tractable dynamic models for SI (Spark Ignited) and HCCI (Homogeneous Charge Compression Ignition) dual mode engines to enable model-based real-time control and optimization of this novel and efficient internal combustion engine. Specifically, we propose a novel SI-HCCI hybrid combustion model that incorporates both SI and HCCI combustions and a new charge mixing model to capture the fluid dynamics and chemical composition of the engine. These two models will be integrated with a feedback structure, that is, the output of the charge mixing model is the input to the hybrid combustion model and the output of the combustion model is fed back to the charge mixing model.
The research will enable the real-time model-based control and optimization of SI-HCCI dual mode engines, which is critical for future clean and efficient automotive propulsion systems. This engine technology will significantly reduce the national oil consumption of both personal and commercial transportations. It will also reduce harmful emissions and mitigate the impact on climate change. This project's approach for developing and validating the hybrid SI-HCCI model can be applied to other type of engines and dynamic systems, where the phenomenological or computational models are not suitable.
This grant allows us to develop accurate yet tractable dynamic models for SI (Spark Ignited) and HCCI (Homogeneous Charge Compression Ignition) dual mode engines to enable model-based real-time control and optimization of this novel and efficient internal combustion engine. Specifically, a new control oriented charge mixing model that captures the dynamic interactions between the residual gas and the fresh charge has been developed. This model allows us to predict the quality and quantity of the mixing of in-cylinder gases as a function of engine valve strategies and operating conditions. This model has been validated with experimental results from an optical engine using a novel graphical analysis method. The developed charge mixing model is further integrated with the SI-HCCI hybrid combustion model developed by our collaborators at MSU. The developed model could enable the real-time model-based control and optimization of SI-HCCI dual mode engines, which is critical for future clean and efficient automotive propulsion systems. This engine technology will significantly reduce the national oil consumption of both personal and commercial transportations. It will also reduce harmful emissions and mitigate the impact on climate change. The project has been a great platform for collaborating with industry partners, training graduate and undergraduate students and disseminating advanced engine modeling and control to practicing engineers and researchers.
