Finite element analysis is used to examine the gap losses that occur in finely laminated nanocrystalline inductor cores under high-frequency operation. The losses are seen to be concentrated in the region of the air gap and the dependence of the losses on key design parameters and operating conditions is explored. The results show that gap losses can be significant in this type of core, creating hot spots around the gap, and the losses are not accurately predicted by established design equations for low-frequency laminated cores. A modified loss equation is proposed. Validation is provided by measurements on a 300-A, 60 kHz inductor.

The emergence of wide-bandgap devices, e.g., silicon carbide (SiC), has the potential to enable very high-density power converter design with high-switching frequency operation capability. A comprehensive design tool with a holistic design approach is critical to maximize the overall system power density, e.g, by identifying the optimal switching frequency. This paper presents a system level design tool that optimizes the power density (volume or mass) of a three-phase, two-level dc-ac converter. The design tool optimizes the selection of the devices, heatsink and passive components (including the design of the line, electromagnetic interference (EMI), and dc-link filters) to maximize the power density. The structure of the optimization algorithm has been organized to reduce the number of potential design combinations by over 99%, and thus, produces fast simulation times. The design tool predicts that when SiC devices are used instead of Si ones, the power density is increased by 159.4%. A 5 kW, 600-V dc-link, three-phase, two-level dc-ac converter was experimentally evaluated in order to confirm the accuracy of the design tool.

A comparison of the performance of graphene‐based supercapacitors is difficult, owing to the variety of production methods used to prepare the materials. To the best of our knowledge, there has been no systematic investigation into the effect of the graphene production method on the supercapacitor performance. In this work, we compare graphene produced through several routes. This includes anodic and cathodic electrochemically exfoliated graphene, liquid phase exfoliated graphene, graphene oxide, reduced graphene oxide, and graphene nanoribbons. Graphene oxide exhibited the highest capacitance of approximately 154 F g⁻¹ in 6 M KOH at 0.5 A g⁻¹ attributed to oxygen functional groups giving an additional pseudocapacitance and preventing significant restacking; however, the capacitance retention was poor, owing to the low conductivity. In comparison, the anodic electrochemically exfoliated graphene exhibited a capacitance of approximately 44 F g⁻¹, the highest of the ‘pure’ graphene materials, which all exhibited superior capacitance retention, owing to their higher conductivity. The cyclability of all of the materials, with the exception of reduced graphene oxide (70 %), was found to be greater than 95 % after 10 000 cycles. These results highlight the importance of matching the graphene production method with a specific application; for example, graphene oxide and anodic electrochemically exfoliated graphene would be best suited for high energy and power applications, respectively.

The More-Electric Aircraft (MEA) underlines the utilization of the electrical powerto power the non-propulsive aircraft systems. Adopting the MEA achieves numerousadvantages such as optimizing the aircraft performance and decreasing operating andmaintenance costs. Moreover, the MEA reduces the emission of the air pollutant gases fromthe aircraft, which can contribute in solving the problem of climate change. However, theMEA put some challenge on the aircraft electrical system either in the amount of the requiredpower or the processing and management of this power. This paper introduces a review forthe MEA. The review includes the different options of generation and power systemarchitectures.

A two-phase buck–boost converter utilizing dual interleaving is presented in this paper. The dual interleaving consists of an interphase transformer that doubles the ripple frequency together with two conventional buck-boost switching arms, mitigating the inductor ripple current and aiding to increase the power density of the converter. A description of the design and selection of the power devices is presented for a 32 kW, 75 kHz dual-interleaved SiC prototype with an interphase transformer, such that a power density of 7.4 kW/kg is achieved. The principle of operation of the circuit is validated by measurements operating the prototype with a 315-385 V supply, a 350 V load and a 97.5% efficiency. The experiments reveal that the interleaved coupled currents are equalized without an active balancer.

Accurately predicting the temperature of semiconductor devices is very important in the initial design of power electronics converter. RC thermal models derived from well-known methods have some ability to predict the temperature. However, the accuracy is boundary condition specific, hence, these methods cannot be used in the reliability analysis. To make the thermal model more accurate and robust the factors contributing to discrepancies need to be analyzed carefully. These are power-module-materials’ non-linear properties, thermal grease layer and the cooling system (i.e., liquid-cooled cold plate). In this work, estimation of accurate RC parameters from FEA thermal model is demonstrated in COMSOL. The electrical model having temperature dependent power loss model is coupled to refined thermal model and solved in a circuit simulator, PLECS. The proposed method is applied in two applications: assessing thermal interaction between IGBTs and anti-parallel diodes in a half-bridge power module, and assessing thermal interaction among the discrete switches in an interleaved bidirectional DC-DC converter. Results show that the impact of material non-linearity, thermal grease layer and cooling boundary conditions are significant for accurate prediction of IGBT and diode temperatures. The proposed model is consistent to FEA results and differs by 2-6.5% comparing to the experimental results.