Parameter Degradation Monitoring and Controller Adaptation Using Digital Twin

Component aging in power electronic converters is detrimental to the reliability of the power-conversion system. The digital twin technology is effective in monitoring components' aging and tracking parameter-drift from the original values. This is crucial in preventing early failure of components and identifying the correct parametric value for controller tuning. This paper proposes a digital-twin based controller adaptation method to make up for the parameter drift due to aging of the converter's passive components. A physical model of a dcdc buck converter and its digital twin model are presented and simulated in MATLAB. A fourth-order Runge-Kutta method is used to model the digital twin buck converter, and Particle Swarm optimization is used to estimate the parameters of the digital twin model based on measurements from the physical and digital twin models. Finally, parametric controller tuning is used to adjust the parameters of the physical buck controller according to the new estimated state.