An Embedded Digital Twin of Power Electronic Converter based on GA-PSO Real-Time Parameter Identification

Power electronic converter is widely used in various fields because it is the basic unit of complex electrical system. However, the faults caused by the degradation of the electrolytic capacitors, inductors, and MOSFET in the power converter greatly reduce the reliability of power electronic converter. The digital twin (DT) can give insightful information about its physical counterpart based on which predictive maintenance can be made to improve the life-cycle management of the power electronics converter. However, it is difficult for the existing DT to accurately represent the behaviors of power converters. An embedded DT of BUCK converter is proposed in this paper based on the generic particle-swarm optimization (GA-PSO) algorithm, based on which the the parameters of the converter can be identified in real time and the states between the DT and the physical converter can be synchronized. The proposed DT as well as the parameter identification method are verified by experimental prototype of Buck converter.