Search Results (3)

Nowadays, numerical simulation methods are advanced and widely used in industry, enabling the modeling of complex systems from printed circuit boards (PCBs) to full power converters. Among many isolated topologies, the phase-shift full-bridge (PSFB) topology is a well-established solution for isolated DC–DC conversion in electric vehicles. Therefore, this paper proposes a broadband electromagnetic compatibility (EMC) modeling methodology for a custom-designed 1 kW gallium nitride (GaN)-based PSFB converter intended for an electric vehicle (EV) DC powertrain. Moreover, the approach combines full-wave electromagnetic simulation with circuit-level simulation, including parasitic effects from PCB layout, power harnesses, and discrete components. Thus, the virtual prototype is assessed within a complete virtual test bench compliant with the standard Comité International Spécial des Perturbations Radioélectriques (CISPR) 25 over the 150 kHz–108 MHz range to capture common-mode (CM) and differential-mode (DM) conducted electromagnetic interference (EMI). Results show that the converter achieves efficiencies of 97.26% in standalone mode and 97.03% when integrated into the full DC powertrain. However, the conducted EMI assessment reveals that both CM and DM emissions exceed CISPR 25 Class 2 limits across the entire spectrum, with excess levels reaching up to 72 dBµV. Therefore, power harnesses significantly increase EMI levels at low frequencies due to the distributed inductance and stray capacitance. Finally, this study demonstrates the value of virtual prototyping for simulation-based EMI prediction in early-stage power converter design. Full article

Automotive-grade GaN power switches have recently been made available in the market from a growing number of semiconductor suppliers. The exploitation of this technology enables the development of very efficient power converters operating at much higher switching frequencies with respect to components implemented with silicon power devices. Thus, a new generation of automotive power components with an increased power density is expected to replace silicon-based products in the development of higher-performance electric and hybrid vehicles. 650 V GaN-on-silicon power switches are particularly suitable for the development of 3–7 kW on-board battery chargers (OBCs) for electric cars and motorcycles with a 400 V nominal voltage battery pack. This paper describes the design and implementation of a 6.6 kW OBC for electric vehicles using automotive-grade, 650 V, 25 mΩ, discrete GaN switches. The OBC allows bi-directional power flow, since it is composed of a bridgeless, interleaved, totem-pole PFC AC/DC active front end, followed by a dual active bridge (DAB) DC-DC converter. The OBC can operate from a single-phase 90–264 Vrms AC grid to a 200–450 V high-voltage (HV) battery and also integrates an auxiliary 1 kW DC-DC converter to connect the HV battery to the 12 V battery of the vehicle. The auxiliary DC-DC converter is a center-tapped phase-shifted full-bridge (PSFB) converter with synchronous rectification. At the low-voltage side of the auxiliary converter, 100 V GaN power switches are used. The entire OBC is liquid-cooled. The first prototype of the OBC exhibited a 96% efficiency and 2.2 kW/L power density (including the cooling system) at a 60 °C ambient temperature. Full article

In order to improve the safety and reliability of airborne power supply and distribution system, a digital twin of a phase-shift full-bridge current doubling rectifier converter based on gallium nitride metal-oxide-semiconductor field-effect transistor (GaN MOSFET) is built. The digital twin can be regarded as virtual symmetry of the real converter. The particle swarm optimization (PSO) algorithm is applied to compare the voltage and current waveforms of the real converter with relative waveforms of its digital model established in simulation software, and the interior parameters of the model are constantly updated until the waveforms of the digital twin coincide with that of the converter. Applications of this digital twin are discussed through experimental verification, and the results show that the digital twin can deduce the parameter value of key components of the converter in the case of soft faults. In the case of hard faults, a back propagating artificial neural net (BP ANN) is trained by data collected from the digital twin, and the BP ANN is able to identify different running states of the converter. The outcomes of this paper present a non-intrusive and high real-time method of condition monitoring and fault diagnosis, which is beneficial to improve the reliability of airborne HVDC power supply system. Full article