Digital Twin Modeling Method of Three-Phase Inverter-Driven PMSM Systems for Parameter Estimation
Wensheng Song, Yuning Zou, Chenwei Ma, Sihui Zhang
Abstract
This article proposes a digital twin modeling method of a three-phase inverter-driven permanent magnet synchronous motor (PMSM) for system parameter estimation offline, which does not require any signal injection or additional sensor and measuring equipment, resulting in a noninvasive approach for the digital modeling and parameter estimation of three-phase PMSM. In the proposed method, a digital twin model that includes the inverter-driven PMSM power stage and the close-loop controller is established in a first step. The key parameters of the PMSM (e.g., stator resistance, stator inductance, and flux linkage) are then obtained with a chaotic particle swarm optimization algorithm by comparing the output data of the digital twin model and the actual physical circuit. To verify the correctness of the proposed digital twin model, a series of experimental studies at different operating conditions are performed. In addition, the effectiveness of the parameter estimation based on the digital twin model has been confirmed, and the accuracy of the estimated parameters is acceptable.