A look-up table-based model predictive torque control of IPMSM drives with duty cycle optimization

Area of Science:

• Electrical Engineering
• Control Systems
• Power Electronics

Background:

• Model Predictive Control (MPC) offers advantages in motor drives like fast response and adaptability.
• Permanent Magnet Synchronous Motors (PMSMs) require efficient control strategies for optimal performance.

Purpose of the Study:

• To present a computationally efficient and low-complexity model-predictive torque control (MPTC) for IPMSMs.
• To reduce switching frequency and computational burden without sacrificing control performance.

Main Methods:

• Developed an MPTC technique using a lookup table independent of flux angle and torque deviation.
• Implemented a maximum torque per ampere (MTPA) for reference current generation.
• Optimized duty cycles using mean torque control to minimize torque and flux ripples.

Main Results:

• Achieved significant reduction in switching frequency and computational load.
• Minimized controller complexity by removing the flux weighting factor from the cost function.
• Experimental validation on a prototype IPMSM drive using a real-time simulator.

Conclusions:

• The proposed MPTC technique offers an efficient and effective solution for IPMSM drives.
• The method demonstrates superior performance compared to conventional MPTC and direct torque control (DTC).
• Validated effectiveness through hardware-in-the-loop (HIL) testing.