Model-based design

mathematical and visual method of addressing problems associated with designing complex control, signal processing and communication systems

Model-based design is a way to create systems by using 'behavioral' and 'implementation' computer models, to simulate how they should work before being built in the real world. It is used in many industries, including aerospace, automotive, and medical sectors. These models can be used for fast testing of ideas. They can verify the success and performance of a system faster and more efficiently than creating any physical products first.

Behavioral Models

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In model-based design, engineers start by creating a computer model that represents a product, often referred to as a "digital twin". This is a behavioral representation of the product, which helps engineers understand how the product should behave in different scenarios, in order to verify that it meets its requirements. This allows designers to simulate and test systems before they are actually built, allowing for a more efficient and effective design process.

Implementation Models

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Once the engineers are happy with the behavior of the digital twin, they create a more specific implementation model. Implementation models provide a more detailed representation of a system's structure and functionality. They often use specific languages or tools to describe the system's components and their interactions. Implementation models can be used to automatically generate code, which helps save time and reduces the possibility of errors.

Product Examples

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Model-based design is often used in embedded systems, such as equipment and medical devices. Engineers might create a digital twin of a pacemaker, and use this to simulate how it will behave in different scenarios. This can help ensure that the pacemaker will function correctly before it is placed in a patient. Automotive companies use model-based design when creating vehicles. A digital twin of an engine may be created to simulate how it will perform in different driving conditions. This can help engineers optimize the design of the engine before building it in the real world.

Advantages

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  • System models can be tested in different scenarios early on, so designers can identify issues before physical products are built in the real world.
  • Existing models can be used as a starting point for new ones, allowing for new products to be developed quicker than would otherwise be possible.
  • Implementation models can be used to automatically generate code, reducing development costs and improving the overall quality of the product.

Disadvantages

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  • Model-based design requires knowledge in computer modeling and simulation, which may be a barrier for some designers or companies.
  • The accuracy of simulations depends on the quality of the models used. If models are not built accurately, they may not provide useful information.
  • As a system becomes more complex, the amount of functionality increases, making it more difficult and time-consuming to create accurate models.