Torque ripple reduction in Permanent Magnet Synchronous Machines using angle-based iterative learning control

Abstract

Permanent Magnet Synchronous Machines (PMSM) are used in many applications, particularly in high-performance drive systems. However, one inherent problem of PMSM is its parasitic undesired torque ripple, which reduces the PMSM performances. Several kinds of parasitic torque ripples are periodic functions of the rotor position. To reduce them, a method called Iterative Learning Control (ILC) seems well suited, but is efficient for only one constant speed chosen by the designer (and all the integer multiples of this speed). To design a solution for a varying speed, an ILC variant named angle-based ILC is proposed, which no longer uses time as the reference, but the angular position. This angle-based ILC can simply be implemented and does not require a heavy computational load. Simulations of a PMSM variable speed drive system and experiments have been done to assess the performances of the proposed technique.