Parameter identification method for brushless DC motors of electrical hoist application

Brushless DC motors (BLDCMs) have been widely adopted across various fields. However, implementing advanced algorithms for high-performance torque control typically relies on accurate mathematical models, requiring precise parameters including inductance, resistance, and back electromotive force (EMF) coefficients. Unlike permanent magnet synchronous motors (PMSMs) that achieve unified mathematical models through coordinate transformation, BLDCMs exhibit distinct mathematical models during commutation and non-commutation phases due to their "three-phase six-step" driving mode. Addressing this challenge, this paper conducts a comprehensive investigation into the mathematical models of BLDCMs across different operational phases and modulation methods, ultimately establishing a unified mathematical framework. Building upon this foundation, a model reference adaptive algorithm-based parameter identification method is proposed. This innovative approach enables offline identification of inductance and resistance parameters, while simultaneously performing online identification of inductance and back EMF coefficients. Experimental results have verified that this method can achieve high identification accuracy for stator inductance, resistance, and back EMF coefficients. Particularly suited for hoist motors requiring frequent start-stop operations, this methodology shows significant practical value in applications demanding robust parameter identification under dynamic operating conditions.