Digital Twin for Degradation Parameters Identification of DC-DC Converters Based on Bayesian Optimization

Abstract

Power electronic circuits have been widely used in various fields, and the requirements for their stability and reliability has increased. Therefore, a degradation parameters identification method of the DC-DC power converters is proposed. The main idea of this method is to use a digital twin to build a DC-DC converter. Under steady and transient operating conditions, the power electronic circuits are simulated to deduce the law of output voltage and inductance current variation of the boost and buck converter, and the operation state of the physical entity is estimated. Degradation characteristic parameters, such as capacitance, inductance, parasitic resistance, and MOSFET on-state resistance, are selected and identified based on the Bayesian optimization. The simulation results verify the validity of the method.