Simulate, Design, and Test Field-Weakening Control Design with Simulink
This webinar provides an overview of developing field-weakening motor control algorithms using Simulink. Field-weakening control is a technique for increasing the speed of an electric motor above its rating. Over-speed capabilities are required for motor applications in electric vehicles and locomotives and industrial automation when higher speed is required and lower torque is acceptable.
To simulate, design, and test field-weakening motor control on embedded hardware, this webinar will demonstrate two workflows. The first approach implements field-weakening control with a linear model and code-generation from the model for deployment on an TI C2000 microcontroller. This workflow uses Motor Control Blockset and is based on equations derived from a PMSM’s parameters. The second approach considers highly nonlinear nature of the machine where PMSM characterization tests are performed on actual hardware using a dyno setup or through an FEA tool. This workflow will show how to create a high-fidelity torque model with an automated workflow for calibrating the optimized lookup tables.
In this webinar, MathWorks engineers will show you how to:
- Demonstrate two workflows for field weakening control
- Automatically generated code of the field-weakening control and spin a PMSM
- Calibration of the field-weakening control lookup table approach
- IPMSM field-weakening control explained on the id-iq plane
- Maximum-flux-based field-weakening algorithms
About the Presenter
Shang-Chuan Lee is a Senior Application Engineer specializing in Electrical system and Industrial Automation industries and has been with the MathWorks since 2019. Her focus at the MathWorks is on building models of electric motor and power conversion systems and then leveraging them for control design, hardware-in-the-loop testing and embedded code generation. Shang-Chuan holds a Ph.D from the University of Wisconsin-Madison(WEMPEC) specializing in motor controls, power electronics, and real-time simulation.
Recorded: 2 Nov 2021
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