Model Based Development Course

Key Highlights:

• Grasp the core principles of model-based development.
• Develop and scrutinize software models.
• Master the tools and techniques essential for model-based development.

Course Content:

1. Theoretical Foundation

• Conceptual Understanding: Dive into the essence of model-based development and its significance in software engineering.
• Real-World Relevance: Explore how this methodology enhances efficiency and quality in software projects.

2. Practical Skills

• Hands-On Exercises: Engage in creating and analyzing models using leading industry tools.
• Project-Based Learning: Apply your skills to real-world scenarios to solidify your understanding.

Modules Breakdown:

MATLAB

• Introduction to MATLAB
• Gain an overview of MATLAB’s capabilities in technical computing.
• Explore its versatile applications in various fields such as engineering, science, and mathematics.
• Installation of MATLAB
• Step-by-step guide to installing MATLAB on different operating systems (Windows, macOS, Linux).
• Understand the different licensing options available.
• Basics of MATLAB
• Familiarize yourself with the MATLAB environment : Command Window, Workspace, and Command History.
• Learn basic operations including arithmetic, logical, and relational operators.
• Discover variables and data types, including numeric, logical, and character arrays.
• Master matrix operations: creation, indexing, and manipulation.
• Programming Basics, Control Flow, and Visualization
• Create and execute MATLAB code using scripting and function files.
• Utilize control flow statements such as conditional statements (if-else) and loops (for, while).
• Generate 2D and 3D plots, customize them, and animate visualizations.

Simulink

• Introduction to Simulink
• Understand Simulink as a graphical programming environment for dynamic systems.
• Learn about its application in control systems design, signal processing, and embedded systems.
• Simulink Editor and Environment
• Navigate the Simulink environment: Model Explorer, Library Browser, and Simulation Manager.
• Create and organize Simulink models effectively.
• Library Browser Overview
• Explore various blocks in the Simulink Library Browser: standard, specialized, and user-defined blocks.
• Drag and drop blocks to build your models.
• Configuration Parameter Settings
• Set up simulation parameters including simulation time and solver options.
• Configure model parameters and variables.
• Modeling Techniques
• Model both continuous-time and discrete-time systems.
• Use Simulink blocks to represent physical components and mathematical functions.
• Create hierarchical models for a modular approach to design.

Stateflow

• Getting Started with Stateflow
• Introduction to Stateflow for modeling state machines and flowcharts.
• Integrate Stateflow with Simulink for comprehensive system modeling.
• Flowchart
• Build flowcharts to represent sequential processes and decision-making steps.
• Use flowchart blocks to model logical conditions and actions.
• Statechart and Hierarchical State Model
• Design statecharts for systems with discrete states and transitions.
• Create hierarchical state machines to manage complex systems with multiple abstraction levels.
• Event-Based Execution
• Implement event triggering and timing mechanisms within Stateflow.
• Model asynchronous and synchronous events effectively.
• Stateflow Parsing and Debugging
• Debug Stateflow charts to identify and rectify errors.
• Use the Stateflow Debugger to step through simulations and inspect variables.

Projects

Algorithm Development for BCM (Body Control Module)

• Develop an algorithm for a BCM that manages various electronic functions in a vehicle, such as lighting, windows, and door locks.
• Create and simulate models to ensure the algorithm functions correctly and efficiently.

Algorithm Development for LCM (Light Control Module)

• Design an algorithm for an LCM that controls the vehicle's lighting system, including headlights, taillights, and interior lighting.
• Use Simulink to model the system, simulate different scenarios, and validate the algorithm’s performance.

Algorithm Development for BIM (Battery Management Unit)

• Develop an algorithm for a BIM that monitors and manages a vehicle’s battery system.
• Create models to simulate battery behavior under various conditions and ensure optimal performance.

MAAB Guidelines Check

• Overview: Understand the MathWorks Automotive Advisory Board (MAAB) Guidelines.
• Compliance Check: Learn how to check models against MAAB Guidelines to ensure compliance with industry standards.
• Implementation: Apply MAAB Guidelines to the developed models for BCM, LCM, and BIM.
• Validation: Validate that the models adhere to MAAB best practices and improve the quality and maintainability of the models.
  
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