基于数字孪生的单相PWM整流器灰箱建模与关键参数监测

Considering that control parameters are difficult to obtain due to industry confidentiality and intellectual property limitations, the existing white-box digital twin (DT) models of single-phase pulsewidth modulation (PWM) rectifiers are difficult to apply in practical applications. Therefore, this article develops a gray-box DT model that can overcome the limitations of unknown control parameters and has higher accuracy. First, the dead-time effect and the equivalent series resistance (ESR) of capacitors are considered in the DT model to improve model accuracy. The operational characteristics of the DT model are closer to the actual system and have more comprehensive health monitoring capability. Then, based on the collected data from actual physical systems under dynamic and static operating conditions, the developed DT model is implemented on an independent server. The key parameters of the model are accurately monitored by using a hybrid algorithm of particle swarm and whale optimization. Finally, the proposed model and its parameter monitoring capability have been validated under different operating conditions, parameters, and control schemes, and the error impact has also been analyzed. This study contributes to the application of noninvasive health monitoring in practical power converters.