85780 - Modeling and Control of Internal Combustion Engines and Hybrid Propulsion Systems M

Course Unit Page


This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Affordable and clean energy Climate Action

Academic Year 2018/2019

Learning outcomes

TThe course has the objective of better understanding modern internal combustion engines for motor vehicles and hybrid propulsion systems, with particular reference to their architecture, functionality, environmental impact and control system. Students develop the ability to model dynamic systems, with a control-oriented approach and with particular application to internal combustion engines and hybrid powertrains (electric, mechanical, hydraulic,…). Finally, the course provides the knowledge necessary to develop control strategies based on physical models of the system (powertrain and / or vehicle), and oriented to the minimization of fuel consumption and pollutant emissions.

Course contents

The first part of the course deals with modeling and simulation of internal combustion engines, with a control-oriented approach.

  • Model objectives: to determine the main engine operating parameters time (or crank-angle based) histories.
  • Mass and energy balance application to the main engine sub-volumes.
  • Crank-angle vs time based simulation. Discrete vs continuous engine models. Intake air mass flow simulation: throttle model. Four-cylinder engine model.
  • Wide Open Throttle (WOT) and load step simulations.
  • Engine control calibration.
  • Simulation of steady-state and transient conditions.
  • Comparison between Alfa-N, Speed-Density and MAF systems for determining intake air mass flow.
  • Lambda closed-loop control. Fuel film model and compensator.
  • Cruise control system. Idle speed control system.

After discussing the main motivations for hybrid powertrains, the second part of the course presents an overview of optimal control theory and introduces a control-oriented model of a hybrid vehicle. Possible solutions for energy consumption minimization are then developed and analyzed in a simulation environment.


Handouts concerning some elements of the program, exercises and examples, are available on AMS Campus. The following list presents the main publications that could be used by the students to deepen specific topics, or to complement their background on the subject.

  • "Introduction to modeling and control of internal combustion engine systems", L. Guzzella, C. H. Onder, Springer, 2010, ISBN 978-3-642-10775-7
  • "Engine Modeling and Control", R. Isermann, Springer, 2014, ISBN 978-3-662-50629-5
  • “Vehicle Propulsion Systems: Introduction to Modeling and Optimization”, L. Guzzella, A. Sciarretta, Springer, 2013, ISBN 978-3-642-43847-9
  • "Hybrid Electric Vehicles - Energy Management Strategies", S. Onori, L. Serrao, G. Rizzoni, Springer, 2016, . ISBN 978-1-4471-6779-2

Teaching methods

The course is held in English. The lessons take place in the classroom, and a personal computer will be used by the instructor to show some PowerPoint presentations and to develop mathematical models. Possibly, each student will use a personal computer running Matlab/Simulink during the simulation and model development sessions. The educational material is uploaded before each lecture on the University online platform.

Attendance is strongly recommended for better learning of concepts and methodologies, but does not affect the final evaluation process.

Assessment methods

Learning assessment is finalized through a final oral examination, which takes place for about 60-90 minutes, answering a few questions in writing (diagrams, equations, diagrams, drawings, ...) and then discussing them with the instructor.

This test is intended to verify the student knowledge about the main subjects of the course. The final vote takes into account the ability to solve problems in the matters discussed during the lectures, and the acquisition of engineering methodologies for assessing the performance of automotive energy conversion systems.

The evaluation, expressed in thirtieths, will be higher the more the student is:

  • autonomous in articulating answers to the questions;
  • exhaustive in explaining the topics;
  • capable of synthesizing the most important parameters and relationships through graphs, sketches, and schematics.

During the exam, students are not allowed to use the lecture notes or other material and they are required to have an identity document.

Teaching tools

Slides and audio-visual supports will be used throughout the course.

Class notes will be distributed to the students through the University online platform before each lecture.

Also the matlab code and simulink models that will be developed and analysed during the lectures will be made available to the students.

Office hours

See the website of Nicolò Cavina