Auto-Optimized Maximum Torque Per Ampere Control of IPMSM Using Dual Control for Exploration and Exploitation

TL;DR

This paper introduces an auto-optimized MTPA control strategy for IPMSM that employs dual estimators for exploration and exploitation, enhancing dynamic performance over extremum-seeking methods, verified through simulations.

Contribution

The paper proposes a novel dual control approach using multiple estimators for improved MTPA control in IPMSM, addressing exploration and exploitation simultaneously.

Findings

Better dynamic performance during speed or load changes.

Effective parameter estimation via multiple recursive least squares estimators.

Simulation results confirm improved control accuracy and robustness.

Abstract

In this paper, a maximum torque per ampere (MTPA) control strategy for the interior permanent magnet synchronous motor (IPMSM) using dual control for exploration and exploitation (DCEE). In the proposed method, the permanent magnet flux and the difference between the $d$- and $q$-axis inductance are identified by multiple estimators using the recursive least square method. The initial values of the estimated parameters in different estimators are different. By using multiple estimators, exploration of the operational environment to reduce knowledge uncertainty can be realized. Compared to those MTPA control strategies based on the extremum-seeking method, the proposed method has better dynamic performance when speed or load varies. The effectiveness of the proposed method is verified by simulations.