ECTS - Automotive Control Systems

Automotive Control Systems (AE423) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Automotive Control Systems AE423 3 1 0 3 5
Pre-requisite Course(s)
MATH 276 and MECE 204
Course Language English
Course Type N/A
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies .
Course Coordinator
Course Lecturer(s)
  • Asst. Prof. Dr. Ali Emin
Course Assistants
Course Objectives To teach the concept of feedback control systems, to explain classical control design and analysis techniques, and to make an introduction to state-space and robust control methods. To apply these control design and analysis techniques to automotive systems by using computer aided tools such as Matlab/Simulink/Octave.
Course Learning Outcomes The students who succeeded in this course;
  • explain the concepts of feedback/feedforward control and compare open-loop vs. closed-loop control
  • derive the differential equations for dynamic systems
  • develop dynamic simulations using computer aided design tools such as Matlab, Simulink, and Octave
  • find the equilibrium points and linearize the differential equations of dynamic systems
  • design controllers with PID, lead-lag and loop-shaping techniques, perform stability analysis of feedback systems using Nyquist, Bode, and root locus techniques
  • apply various control techniques to design automotive control systems such as active suspension system design, vehicle stability control, and autonomous steering
Course Content Concept of feedback; mathematical model of dynamic systems; transfer functions (Laplace transform) and state-space representations; frequency domain design techniques; root locus, Nyquist, and Bode diagrams; vehicle stability control, active suspension control, and autonomous steering applications.

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 History of control systems, concept of feedback, open-loop vs. closed-loop control
2 Mathematical modeling of dynamic systems and their simulations in Matlab, Simulink, and Octave environments
3 Linearization of the equations of motion
4 Frequency response function, Nyquist and Bode plots
5 Gain and phase margins, root locus design technique
6 Root-locus and PID techniques
7 Loop-shaping and lead-lag design techniques
8 State-space representations
9 Midterm exam
10 Developing simulation environment for vehicle dynamic model
11 Designing and simulating vehicle stability controller
12 Design of active suspension system
13 Evaluation of active suspension controller with simulation
14 Autonomous steering design, evaluation of autonomous steering with simulations
15 Final exam

Sources

Course Book 1. Automotive Control Systems, 1st Edition, Galip Ulusoy, Huei Peng, Melih Çakmakçı, Cambridge University Press, 2012.
2. Automotive Control Systems: For Engine, Driveline, and Vehicle, Uwe Kiencke, Lars Nielsen, Springer-Verlag, Berlin Heidelberg, 2005.
3. Modern Control Engineering, 5th Edition, Katsuhiko Ogata, Pearson, 2010.
Other Sources 4. Öğretim elemanı tarafından sağlanan ders notları ve diğer kaynaklar

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments 5 25
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 45
Toplam 7 100
Percentage of Semester Work 0
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Ability to expand and get in-depth information with scientific researches in the field of mechanical engineering, evaluate information, review and implement.
2 Have comprehensive knowledge about current techniques and methods and their limitations in Mechanical engineering.
3 To complete and apply knowledge by using scientific methods using uncertain, limited or incomplete data; use information from different disciplines.
4 Being aware of the new and developing practices of Mechanical Engineering and being able to examine and learn when needed.
5 Ability to define and formulate problems related to Mechanical Engineering and develop methods for solving and apply innovative methods in solutions.
6 Ability to develop new and/or original ideas and methods; design complex systems or processes and develop innovative/alternative solutions in the designs.
7 Ability to design and apply theoretical, experimental and modeling based researches; analyze and solve complex problems encountered in this process.
8 Work effectively in disciplinary and multi-disciplinary teams, lead leadership in such teams and develop solution approaches in complex situations; work independently and take responsibility.
9 To establish oral and written communication by using a foreign language at least at the level of European Language Portfolio B2 General Level.
10 Ability to convey the process and results of their studies systematically and clearly in written and oral form in national and international environments.
11 To know the social, environmental, health, security, law dimensions, project management and business life applications of engineering applications and to be aware of the constraints of their engineering applications.
12 Ability to observe social, scientific and ethical values in the stages of data collection, interpretation and announcement and in all professional activities.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 14 3 42
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 14 3 42
Presentation/Seminar Prepration
Project
Report
Homework Assignments 5 3 15
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 10 10
Prepration of Final Exams/Final Jury 1 16 16
Total Workload 125