Online MTPA Tracking of IPMSM Based on Min-Max Optimization

This paper proposes an online maximum torque per ampere (MTPA) tracking algorithm for an interior permanent-magnet synchronous motor (IPMSM) using sequential quadratic programming (SQP). This paper formulates the MTPA problem as a min-max problem of the Lagrangian function. Based on the formulation, the proposed algorithm tracks the MTPA current operating point in real-time while considering magnetic saturation, cross-magnetization, and the effect of flux linkage variation caused by the temperature variation. Furthermore, the proposed algorithm does not require motor parameters, premade look-up tables (LUTs), and gains that need to be tuned. The performance of the proposed method is verified by experimental results with a 25 kW IPMSM. By applying the proposed algorithms for generating current reference, fast MTPA tracking is achieved even at the magnetically saturated operating region.