Internal Combustion Engine Modeling (ME7440)

Course Description

This graduate course develops competence in the thermo-fluid modeling and simulation of Internal Combustion Engines, and is oriented to students and practicing engineers with interest in developing their own models or utilizing commercial simulation tools for conducting virtual engine design, performance analysis, optimization and control.

The course focuses on physics-based engine simulation for performance analysis and optimization, covering the theory, governing equations and related methods of implementation to predict the behavior of the most important engine systems and processes.  In addition, the course provides practical experience with various modeling methods (mean-value, crank-angle resolved, gasdynamic models). During this course, the students will progressively build a crank-angle resolved model of a single cylinder IC engine (in Simulink), and learn to use a commercial simulation software (GT-Power).

Undergraduate background in internal combustion engine fundamentals and working knowledge of Matlab and Simulink is required.



Upon completion of this course, participants will be able to:

  • Understand the physical principles and governing equations describing the thermodynamics and gas dynamics of internal combustion engines;
  • Develop a complete crank-angle resolved model (Matlab/Simulink) of engine air path, combustion, heat transfer and torque output, and utilize such model to perform simulation, analysis and optimization;
  • Understand in depth the mathematical framework and key assumptions/limitations of one-dimensional gasdynamic models;
  • Develop competence in the use of commercial simulation tools (GT-Power) to conduct performance analysis, optimization and control of IC engines.



Marcello Canova
Marcello Canova is associate professor of Mechanical and Aerospace Engineering at The Ohio State University, and associate director for Graduate and Continuing Education at the Center for Automotive Research. His research focuses on the optimization and control of propulsion systems, including internal combustion engines, hybrid-electric drivetrains, energy storage systems and thermal management.

Canova’s work in energy optimization of advanced powertrains has led to significant fuel economy benefits and has been implemented in production programs by major OEMs. In addition, he has published over 110 articles in refereed journals and conference proceedings and received, among others, the SAE Vincent Bendix Automotive Electronics Engineering Award (2009), the SAE Ralph E. Teetor Educational Award (2016), the NSF CAREER Award (2016), the Lumley Research Award (2016) and the Michael J. Moran Award for Excellence in Teaching (2017).






"This was one of the best classes I've ever taken. To build from scratch a Matlab model to represent an engine was great. The structure of the course is well planned and every subject is taught just as needed for the projects and in the end all comes together with a GT-Power model."