This $166,992 National Science Foundation project grant supports the development of control-oriented modeling and predictive control tools for high-efficiency, low-emission natural gas engines through a collaboration between Clemson University, the University of Georgia, and Cummins Inc. The National Science Foundation Engineering Directorate aims to improve engineering research and education through funding such as this award provided under the Congressionally Designated CFDA program for Engineering.
Specifically, the project will develop innovative modeling and stochastic predictive control design tools to address control challenges for advanced dual fuel natural gas engines and other nonlinear, stochastic dynamic systems. Outcomes include characterizing engine dynamics, building the first physics-based control-oriented model for such engines, developing new analytical tools combining machine learning and multivariate methods, and constructing and validating combustion controllers. The tools and demonstrated engine testbed applications have potential benefits for power generation, automotive, and other industrial sectors that widely utilize combustion engines.