Model Based Development

Understand the architecture and optimization of generated embedded code.

Learn to customize data characteristics and storage classes for specific application needs.

Gain skills in testing and deploying generated code on target hardware.

Explore advanced integrations, such as device drivers and reusable subsystems.

Proficiency in Simulink and Embedded Coder for production code generation.

Expertise in optimizing and profiling code for performance.

Integration of generated code with external projects and standards.

Deployment of real-time embedded systems.

HEV powertrain modeling and vehicle dynamics.

Battery systems and energy management strategies.

Control strategies for hybrid vehicle operation.

Simulation and performance analysis using driving cycles.

Model-based design using MATLAB, Simulink, and Simscape.

Development and optimization of energy management algorithms.

Simulation, debugging, and validation of HEV models.

Supervisory control design with Stateflow for mode switching.

Fundamentals and basics of matlab scripting.

Modeling continuous and discrete systems in Simulink.

System development and Validation in MATLAB using model based approach.

Introduction to ADAS and Levels of autonomy in vehicles.

Embedded Software Development.

Requirement Analysis.

Verification and Validation.

Practical examples from Automotive Industry.

Modeling electrical, mechanical, and hydraulic systems.

Integrating Simscape models with Simulink.

Simulating energy transfer between physical domains.

Creating custom components using the Simscape language.

Building and simulating Simscape models.

Interpreting and analyzing Simscape block diagrams.

Designing multidomain systems with subsystems and parameters.

Developing user-defined physical components for specific applications.

Designing flowcharts, state machines, and hierarchical models.

Implementing parallel and component-based Stateflow models.

Integrating events, truth tables, and functions in state diagrams.

Leveraging temporal logic and transition tables for system designs.

Creating state machines and flowchart models.

Using events and logic operators for dynamic system control.

Developing reusable and modular components in Stateflow.

Applying graphical and tabular modeling techniques.

Simulating and analyzing continuous, discrete, and hybrid systems.

Designing hierarchical models with reusable components.

Utilizing conditional execution for control signals.

Creating libraries for modularity and code sharing.

Developing and simulating dynamic Simulink models.

Applying solver settings for performance optimization.

Constructing subsystem references and model hierarchies.

Managing and distributing custom libraries.

Types and characteristics of batteries used in EVs.

Modelling battery performance, capacity, and life cycle with MATLAB and Simulink.

Understanding the function of Battery Management Systems (BMS).

Simulating and analysing battery behaviours to optimize performance.

Creating and simulating battery models for EV applications.

Using MATLAB and Simulink for advanced battery system modelling.

Designing systems to optimize battery life and performance.

Analyzing battery performance data and implementing optimizations.

Understand EV powertrain components and their integration.

Learn to design real-time control systems for EVs.

Study power, efficiency, and thermal management in electric vehicles.

Use MATLAB/Simulink for modeling and simulating EV control systems.

Develop and implement control algorithms for EV systems.

Simulate and test EV systems for performance optimization.

Integrate EV subsystems for efficient operation.

Apply energy management strategies to improve range and efficiency.