This paper presents a digital twin (DT)-based fault recovery method for power electronic converter systems. The method employs a prediction accelerator with a DT model for each subsystem of the converter system and feeds back the predicted system state to the controller. The paper demonstrates that the method can recover from faults such as load and input voltage variations in realtime and can integrate with hardware in the loop for future applications and comparing with other advanced control methods. The paper also highlights the benefits of the method in terms of scalability, replaceability and modularity for power electronic systems.

This study evaluates the full-linear transfer function model for the dual-active-bridge with the impedance-based small-signal averaged model. Besides, for the better implementation on the FPGA, a discrete-time state-space model has been developed. The model matching comparison of non-linear, full-linear, switching and state-space models has been done. In this paper, each mode of single and cascade connection of dual active bridge have been evaluated and compared.

Employing high frequency (HF) transformer in DC-DC converter is a popular strategy in power electronic industry. Equivalent circuit model of transformer in HF Dual Active Bridge (DAB) converters is investigated along with its impact on power transfer characteristic for Single Phase Shift (SPS) and Extended Phase Shift (EPS) modulation. Equivalent branches of magnetizing inductance allocated in primary and secondary side can inject the inductive current at switching instants to extend Zero Voltage Switching (ZVS) range. ZVS maps are proposed. Based on the power transfer characteristics and ZVS maps, an Advanced Extended Phase Shift (AEPS) modulation method with modified coupling relationship for phase shift is proposed to reduce the current stress and improve the voltage utilization. Finally, AEPS modulation is implemented in PLECS simulations to verify the analyzation presented.

Higher voltage DC distribution systems are being used or considered for aircraft, ship and EV/HEV automotive applications and are required for photovoltaic (PV) systems. Fault detection and location in these systems can be very challenging and electrical arcs can cause significant damage such as electrical fires. Therefore, detecting arc faults for DC systems is receiving considerable attention in the research community. Non-contact arc characteristics and arc detection mechanisms in DC systems are addressed in this paper through theoretical development and experimental tests.