Full Parameter Identification of Permanent Magnet Synchronous Motor Based on Signal Injection

Permanent magnet synchronous motors (PMSMs) are playing an increasing crucial role in industrial applications, where inaccurate system parameters can affect control performance and even threaten system stability. This paper aims to tackle the complex and cumbersome recognition algorithms for electrical and mechanical parameters of the PMSMs, which often result in long identification duration and low precision. We propose a full-parameter identification algorithm for PMSMs based on signal injection. This algorithm is simple and effective, easy to deploy, has a short identification duration, and high precision. It can achieve full parameter identification of resistance Rs, d-axis inductance Ld, q-axis inductance Lq, permanent magnet flux ψf, moment of inertia J, viscous damping coefficient Bm, and Coulomb friction coefficient Cm, contributing to the design and development of a high-performance PMSM servo control system. Firstly, this paper presents the identification algorithms for electrical and mechanical parameters. Then a simulation model is built using Maltab/Simulink. Finally, experiments are conducted on a 1.5kW built-in PMSM experimental platform. Both the simulation and experiments have verified the feasibility and effectiveness of the proposed method.