Engineers developing motor control, battery management, and power conversion systems reduce their efforts by using MATLAB®, Simulink®, and Model-Based Design (3:17) . These engineers develop their software algorithms before implementing them in hardware by:
Learn more about motor and power control design with Simulink:
Designing Supervisory and Closed-Loop Control Algorithms
Simulating Electrical Systems
Validating and Implementing Control Algorithms
Motor control algorithms regulate speed, torque, and other performance characteristics. These algorithms help with energy efficiency, precision control, and system protection. You can use simulation to evaluate control algorithms in order to determine the suitability of motor controller designs. This reduces the time and cost of algorithm development before you commit to expensive hardware testing.
A workflow for developing motor control algorithms using Model-Based Design involves:
For efficient power conversion and control, you need to control the action of IGBTs, power MOSFETs, and other solid-state electronics. As the number of consumer, commercial, and industrial products employing power electronics increases, it becomes more important to understand the interaction of digital control algorithms, power electronics, and the balance of the electrical system early during development, before hardware testing begins. Using simulation, you can develop power electronic control systems in less time, and you can design control algorithms and verify that your overall system achieves the specified efficiency and performance.
A workflow for developing power electronics control algorithms using Model-Based Design involves:
Battery management systems are an essential component of electric vehicle, grid storage and power backup, consumer goods, portable medical device, and aerospace systems. They depend on embedded control systems that regulate charge/discharge scheduling, estimate state-of-charge, set safety cut-off limits, and implement cell balancing. A proven approach for developing these systems accurately includes simulating the control laws within the electrical system. However, one challenge is in creating a battery model that balances accuracy and simulation speed.
A workflow for developing battery management control algorithms using Model-Based Design involves:
Solar inverters contain control algorithms for maximum power tracking, grid voltage and frequency synchronization, and anti-islanding protection. You need these algorithms in order to ensure optimal power delivery under changing solar irradiance. You can use simulation to evaluate control algorithms to determine the suitability of the inverter design. This reduces the time and cost of algorithm development before you commit to expensive hardware testing. A workflow for developing solar inverter control algorithms using Model-Based Design involves: