A digital twin based approach for parameters identification of a three-phase inverter and sensors

In the development of converters, ensuring the reliability of critical components has always been a very important issue. The emergence of digital twin technology provides an innovative solution for efficient, non-invasive and reliable condition monitoring, so the concept of digital twin has attracted extensive attention from the academic community at home and abroad after it was proposed. In this paper, a method for monitoring the key parameters of a three-phase two-level inverter and current sensors based on digital twin technology is proposed. First, a digital twins built that included the key parameters o f the three-phase inverter and current sensors. Secondly, an objective evaluation function was constructed. Then, the adaptive particle swarm optimization (APSO) algorithm is used to update the key parameters to reduce the difference between the twin model and the actual circuit, enabling the monitoring of the key parameters of the entire inverter system. Finally, the effectiveness of the method and the accuracy of parameter monitoring are verified by simulation.