# ​Course Outlline

Based on the Simulink for System and Algorithm Modeling outline, this course is for automotive engineers who are new to system and algorithm modeling and teaches attendees how to validate designs using Simulink®. Topics include:

• Creating and modifying Simulink models and simulating system dynamics

• Modeling continuous-time, discrete-time, and hybrid systems

• Modifying solver settings for simulation accuracy and speed

• Building hierarchy into a Simulink model

• Creating reusable model components using subsystems, libraries, and model references

# Prerequisite

MATLAB Fundamentals for Automotive Applications.

# Day 1 of 2

Creating and Simulating a Model

Objective: Create a simple Simulink model, simulate it, and analyze the results.

• Introduction to the Simulink interface

• Potentiometer system

• System inputs and outputs

• Simulation and analysis

Modeling Programming Constructs

Objective: Model and simulate basic programming constructs in Simulink.

• Comparisons and decision statements

• PWM conversion system

• Zero crossings

• MATLAB Function block

Modeling Discrete Systems

Objective: Model and simulate discrete systems in Simulink.

• Discrete signals and states

• PI controller system

• Discrete transfer functions and state-space systems

• Multirate discrete systems

Modeling Continuous Systems

Objective: Model and simulate continuous systems in Simulink.

• Continuous states

• Throttle system

• Continuous transfer functions and state-space systems

• Physical boundaries

# Day 2 of 2

Solver Selection

Objective: Select a solver that is appropriate for a given Simulink model.

• Solver behavior

• System dynamics

• Discontinuities

• Algebraic loops

Developing Model Hierarchy

Objective: Use subsystems to combine smaller systems into larger systems.

• Subsystems

• Bus signals

Modeling Conditionally Executed Algorithms

Objective: Create subsystems that are executed based on a control signal input.

• Conditionally executed subsystems

• Enabled subsystems

• Triggered subsystems

• Input validation model

Combining Models into Diagrams

Objective: Use model referencing to combine models.

• Subsystems and model referencing

• Model referencing workflow

• Model reference simulation modes

• Model workspaces

• Model dependencies

Creating Libraries

Objective: Use libraries to create and distribute custom blocks.

• Creating and populating libraries