This paper presents an optimization-based methodology for sizing the passive components of a modular multilevel converter (MMC) intended for a 150 kW aircraft application. The converter is used as an active rectifier and interfaced with a variable-frequency (500 Hz – 1650 Hz) permanent magnet synchronous machine (PMSM) to generate a 800 VDC on board aircraft distribution bus. A proof-of-concept (POC) of 10 kW has been built and experimentally tested to validate the proposed methodology.

This paper proposes a methodology that integrates machine learning techniques into harmonic load flow analysis for electrical distribution networks. Nonlinear loads are represented as black-box models, where the harmonic components of the load currents are estimated based on the frequency spectrum of the supply voltage and the equivalent impedance. This eliminates the need for prior knowledge of internal architecture or parameters of the loads, including power converters and control algorithms. The proposed workflow encompasses dataset construction, data preprocessing, and the training and evaluation of three machine learning models using appropriate performance metrics. Unlike conventional methods, the proposed approach explicitly captures the interactions between converter or nonlinear load currents and grid operating conditions. The methodology is validated using a typical CIGRE low-voltage benchmark network, where the apparent power of the machine learning based model is progressively increased. During this process, numerical convergence challenges arise and are effectively addressed through an alternative mathematical framework describing the coupling between the harmonic load flow and machine learning models. This reformulation not only guarantees convergence but also significantly improves computational efficiency. A comparison with time-domain simulations confirms that the frequency-domain results converge toward the physical solution within an acceptable error margin. This demonstrates the robustness and accuracy of the proposed approach, highlighting its potential to overcome key limitations of existing harmonic analysis models.

This article explores the modeling of inter-turn short circuits (ITSCs) in segmented permanent magnet synchronous machines, with a focus on highly coupled segmentation (HCS) and multisector segmentation (MSS) of its winding. It introduces a specific approach, providing a consistent framework for analyzing this phenomenon when the segmented drive operates in power-sharing mode. The study presents a comprehensive model for analyzing ITSC faults regardless of the segmentation technology implemented. This model is compared with data extracted from an experimental bench designed in the laboratory for this study. The analysis shows an excellent fit of the model to the experiment. Also, the analytical structure implemented enables comparing the impact of power sharing on segmented structures. The main results reveal that, contrary to HCS, MSS configurations exhibit greater sensitivity to power-sharing variations, particularly depending on the degrees of freedom of the segment where ITSC fault occurs.

The transportation industry (automobile, aerospace) is undergoing a significant shift towards higher voltage supply, to increase embedded power. Increasing the voltage can lead to an increase in the occurrence of partial discharges which have a deleterious impact on the insulators, and therefore of the system lifetime. The current study investigates two electric drives architecture, namely first a combination of a conventional motor with a single inverter and, second, a multi-Three-Phase machine based on highly coupled windings and combined with dedicated sub-inverter. The latter is based on CTAF concept (Chaîne de Traction à Alimentation Fractionnée for Electric Drive based on Segmented Power Supply). This innovative power supply concept is presented in the case study section. According to the goal of this study, a 54-turns coil is developed and modelled as the equivalent circuit, while the related lumped parameters are determined by a frequency-dependent electrostatic and magnetostatic COMSOL simulation. Subsequently, a MATLAB/SIMULINK simulation of the equivalent electric circuit enables assessing the voltage potential distribution. The latter is injected as input into the COMSOL electrostatic simulation to compute the electric field. Consequently, the maximum voltage supply without breakdown is determined, for both studied cases. The comparative study concludes that, between the two case studies analyzed, the minimum among the maximum voltage supplies without breakdown is observed in the system powered with the CTAF approach.

Multiple-Active Bridge (MAB) converters enable energy to be transferred between several sources and loads via a multi-winding magnetic coupler. This coupler plays a key role in the system’s performance, as its sizing determines the power flows. This work proposes an original methodology based on multi-fidelity kriging, combining a small number of accurate 3D simulations with a large number of less expensive 2D simulations. The results show that this approach improves the predictive accuracy for the majority of the magnetic model parameters, particularly when few 3D simulations are available. These metamodels have been validated by comparison with LTSPICE simulations, confirming their relevance for the rapid dimensioning of MAB converters.

This paper proposes a new Energy Management Strategy (EMS) for Fuel Cell Electric Vehicles (FCEVs) that optimizes energy efficiency and fuel cell durability, while remaining implementable in real-time. The approach uses an analytical solution of the minimization problem for fuel consumption, which provides the constant fuel-cell power required to bring the state of charge (SoC) from its initial value to its desired final value. This global optimization, done for the initial route prediction, is included in a new control framework with a SoC regulator. This controller tracks the desired SoC evolution when the actual vehicle route is perturbed, while respecting constraints that preserve fuel cell longevity by 40 % compared to equivalent SoC controllers in the literature. The performance of the proposed EMS is assessed using Matlab/Simulink simulations for several case studies based on standard and perturbed driving cycles, showing up to a 10 % reduction in hydrogen consumption and up to a 50 % improvement in fuel cell lifespan compared to other energy management strategies.

The Fuel Cell Electric Vehicle is one of the solutions envisaged reducing greenhouse gas emissions in the transportation sector. Generally, a fuel cell is connected to a second energy source, such as a battery. The connection is realized using an interleaved boost converter. In recent years, a new converter candidate has emerged in the literature: the partial power converter. This converter is intended to connect the fuel cell to the other parts of the vehicle instead of the classical boost converter. Simulations are needed to assess the energetic performance of the partial power converter integrated to the vehicle. A comparison with the boost converter is performed with the same constant efficiency. This study demonstrates a theoretical reduction of 4% of the losses to the advantage of the partial power converter.

The current charging technology for electric vehicles consists of plugging the cable from the AC utility to charge the batteries. This requires heavy gauge cables to connect to electric vehicles, which can be difficult to handle, presents tripping hazards, and is prone to vandalism. In addition to these inconveniences, electric vehicles must be immobilized for hours before being fully charged. Dynamic wireless power transfer has been studied worldwide as a promising technology. It is safe and convenient and allows electric vehicles to charge while moving. To improve the efficiency of a dynamic wireless power transfer system, the magnetic coupling coefficient must be maximized between the primary pad, which is integrated into the road, and the secondary pad installed in the electric vehicle. This article presents a parametric optimization of the ferrite structure used for a 3 kW dynamic wireless power transfer prototype. Different ferrite configurations are compared while studying the effect of the parameter values on their magnetic coupling coefficient. Finally, the proposed structure was validated during the experimental test, and its coupling coefficient was improved by 26% compared to the original structure.

Power electronic-based non-linear devices inject harmonic current into the distribution grids they are connected to. Their injection depends on the preexisting distortions of their supply voltage and on the grid upstream impedances. Electromagnetic Transient (EMT) techniques capture quite accurately the non-linear relationships between the network and the device harmonic injections thanks to detailed time models. Their downsides are that detailed power electronic models are seldom available to grid operators, and when available, the simulations are time- and resource-consuming as new EMT simulations are required whenever the network conditions evolve. In recent years, machine learning metamodels (MLM) have been able to accurately predict the behavior of non-linear systems. We apply this approach to model harmonic sources in the frequency-domain and present in this paper how MLM accurately predict the harmonic currents of various devices. The proposed technique is validated over a database built with a series of EMT simulations performed with various voltage and impedance conditions.

To reduce the time-to-market of electric vehicles, fast and accurate energetic simulations are needed. This paper aims to propose a fast computational dynamic model that allows a good compromise between accuracy and computation time while respecting the dynamics of the system. Its accuracy and computation time are evaluated compared to conventional static and dynamic models. The results show that the proposed dynamic model estimates the same energy consumption as the traditional dynamic model for a computation time 85 times faster. The computation time of the static model is four times faster than the proposed model, but the accuracy is reduced.

Recently, the number of electric vehicles (EVs) is increasing due to the declining of oil resources and rising of greenhouse gas emission. However, EVs have not received wide acceptance by consumers due to the limitations of the stored energy and charging problems in batteries. The dynamic or in motion charging solution becomes a suitable choice to solve the battery related issues. Many researchers and vehicle manufacturers are working to develop an efficient charging system for EVs which is based on magnetic emissions to transfer power. These emissions must be evaluated and compared to limits specified by standards (in and outside the vehicle) in order to not cause harmful effects on their environment (humans, pets, electronic devices...). This paper presents an efficient method for modeling electromagnetic emission in near field and sizing a magnetic shield for a wireless power transfer (WPT) system for EVs. A model based on elementary magnetic dipoles is developed in order to obtain the same radiation as the real WPT coil. This model is used to size a magnetic shield which will be placed under the vehicle to protect human body from magnetic emissions. The obtained shielding plate allows to respect the standards of magnetic emission by bringing a decrease of 43 dB to the levels of magnetic fields. This approach is experimentally validated.

Power electronic-based devices inject harmonic perturbations in electrical networks and are thus a concern for network operators who must ensure that the harmonic injections and the resulting voltage disturbances are kept within acceptable limits. In this paper, we show that time domain (TD) methods can be useful in preliminary harmonic source modelling to derive the simulated models. Using TD SIMULINK models of our devices, we find the most influential internal and external parameters to be considered when the device is operating in a pre-existing harmonic environment and we generate datasets that can be used for training machine learning (ML) algorithms. We propose here three ML techniques to predict the harmonic currents originating from most widespread power electronic devices such as Light Emitting Diodes (LED) lamps and Electric Vehicle (EV) chargers, and compare them with TD models. The accuracy of all these models regarding their harmonic currents prediction capability is assessed under constantly evolving supply conditions.

We present an electric traction chain with segmented power supply for automotive applications. The concept is to split the windings of the electrical machine into sub-windings by bundle of turns. Each sub-winding is then fed by an independent low-voltage power electronics converter. We describe here the concept in details and discuss its advantages and its drawbacks. This allows us to identify the scientific and technical obstacles that will need to be solved.

Recently, the number of electric vehicles (EVs) is increasing due to the decline of oil resources and the rising of greenhouse gas emissions. However, EVs have not received full acceptance by consumers due to the limitations of the stored energy and charging problems. The dynamic or in-motion charging solution has become a suitable choice to solve the battery-related issues. Many researchers and vehicle manufacturers are working to develop an efficient charging system for EVs. In order to improve the efficiency of the dynamic wireless power transfer (DWPT), the electromagnetic coupling coefficient between the two parts of the coupler must be maximized. This paper was dedicated to find the optimal topology of a magnetic coupler with the best coupling factor while taking in consideration the displacement and the misalignment of the EV. The article is introduced by developing a methodology for characterizing the electrical parameters of couplers, followed by a comparative study of different forms of coils suitable for dynamic charging of electric vehicles. The particularity of the proposed study concerned the overall dimensions, or the areas occupied by the windings of the coils remaining the same for all the chosen shapes and corresponding to the surface that is actually available under the EV. Simulation and experimental tests were carried out to validate the proposed study.

Cet article presente le concept CTAF - Chaine de Traction a Alimentation Fractionnee. Ce concept s'articule autour des machines polyphasees, dont les enroulements des phases sont fractionnes en sous-enroulements. Chaque sous-enroulement est alimente par un convertisseur d'electronique de puissance basse tension independant. L'objet de cette publication est de decrire ce concept, d'en exposer les atouts, ainsi que les limites.

This paper compares the operating of a three-phase, high frequency, series resonant converter (700 kHz, 15 V-15 V, 100 W) with balanced and unbalanced transformer. Analytical equivalent single phase circuit modelling of three phase transformer is described for both cases. A new design of planar transformer is proposed which allows for a better balancing of the magnetomotive force. The sizing method of such transformer is detailed.

This paper presents an optimization methodology for the design of magnetic components embedded in aeronautical structures. We want to realize a multi-objective optimization of an inductance, taking into account some physical phenomenon that are not easily described with mathematical formulations, and to set up a methodology that allows us to harvest optimization time. We will use, for that purpose, analytical formulations, Finite Element Analysis (FEA), and a neural network to reduce the time consumption of components evaluation.