Digital Twin-Based Multi-Parameter Coordinated Identification Method for Three-Phase Four-Leg Converter

To address the complexity of multi-parameter degradation identification in three-phase four-leg (3P4L) converters, this paper proposes a digital twin-based identification method for 3P4L converters, which can simultaneously identify multi-degradation parameters in a coordinated manner. Firstly, a discretized model encompassing the main circuit and control strategy of a 3P4L converter is constructed, which is based on the topology and component characteristics. Secondly, a fourth-order Runge–Kutta (RK4)-based digital twin model of the 3P4L converter is developed on the discretized physical model. Finally, a 3P4L full-simulation and hardware-in-loop (HIL)-based verification platform based on StarSim is built, in which the Levy flight–Whale Optimization Algorithm (LF-WOA) is employed to iteratively identify the multi degradation characteristic parameters of the digital twin model. The results demonstrate that the proposed digital twin model and parameter identification method can achieve the simultaneous identification of multiple parasitic parameters, such as on-state resistance, capacitance, and inductance, with an identification accuracy exceeding 90%.