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Simulink for Automotive System Design
Must-to-Attend for Beginners
Simulink for Automotive System Design
Learn the fundamentals of Simulink. Explore building and simulating models, developing hierarchy, and sharing designs
Complimentary Services: Post training email support & 1-hr consultation session within 1 month after the course completion!
Course
Highlights
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
Who Should
Attend
Engineers in Automotive industry who are new to the Simulink environment
Course
Prerequisites
MATLAB Fundamentals for Automotive Applications
Course
Benefits
Upon the completion of the course, the participants will be able to:
- create, modify and simulate dynamic systems using Simulink
- build continuous, discrete, algebraic and logic systems
- understand solver setting
- build hierarchy into Simulink model
- create reusable model components
Partners
Upcoming Program
- Please keep me posted on the next schedule
- Please contact me to arrange customized/ in-house training
Course Outline
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
- Vector signals
- 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
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
- Masks
- Getting help
- Creating and running scripts
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
- Managing library links
- Adding a library to the Simulink Library Browser
