Using Model-Based Design in the Digital Control of Electrical Drives Laboratory

The complexity of embedded systems in industry is increasing, transforming how engineers design them. Advanced control strategies like predictive, regressive, or genetic algorithms are now implemented in small devices like Systems on Chip (SoC), despite their significant impact on CPU load. Advances in microelectronics have enabled the integration of powerful, low-cost controllers into embedded systems. However, programming these complex systems poses challenges. Creating new functions often requires extensive code, making it difficult to manage, maintain, and debug. To address this, companies have adopted Model-based Design Development (MbD) to streamline system and software development. Widely used in the automotive industry, MbD reduces project costs and accelerates development by integrating modeling, simulation, automatic code generation, and testing across all stages of the V-Cycle. Engineers can simulate system behavior, generate code, and test implementations in offline (MiL) or online (SiL) environments. This paper explores a way of using the MbD approach in student laboratory applications. This will provide students with an initial introduction to the subject before they engage in industry trials to understand and apply MbD.