The acoustic noise emitted by electric motors results from complex multiphysics interactions involving electrical, electromagnetic, mechanical, rotor dynamic, and acoustic phenomena. Traditional modeling approaches often rely on chained simulations, sequentially linking electrical excitation, Maxwell stress computation, stator vibration, and radiated noise. However, these approaches are limited by the absence of strong coupling with the rotor. This paper investigates the impact of strong coupling between Maxwell stress distributions and rotor dynamics, and its influence on electromagnetic forces. A time-domain simulation framework is developed, combining an analytical subdomain-based model for the electromagnetic field with a one-dimensional finite element method for rotor dynamics. The study compares results obtained from weak, intermediate, and strong coupling strategies. The findings highlight the conditions under which weak coupling becomes insufficient, particularly depending on the rotor mechanical stiffness. This work provides new insights into the validity range of classical weak coupling methods and underscores the necessity of strong multiphysics interaction modeling for accurate noise prediction in electric machines. This also shows that for flexible rotors, the standard weak coupling approach significantly underestimates excitation levels. Thus, a strong coupling approach is necessary to avoid underpredicting magnetic noise and to ensure the vibroacoustic reliability of high-speed machines.

This work investigates the vibratory behavior of single-phase magnetic cores made of grain-oriented electrical steel (GOES) through numerical and experimental approaches, focusing on magnetostrictive effects. A controlled non-shifted core configuration is studied. It prevents the magnetic flux circulation between sheets, ensuring deformations are solely attributed to magnetostriction. Modal analysis, finite element modeling, and an inverse force identification method are employed to determine equivalent magnetostrictive forces with validation through experimental measurements.

The flux-barrier rotor topology, widely recognized as optimal for synchronous reluctance machines (SynRM), has well-established design parametrization guidelines. However, these conventional design rules face challenges when applied to small-diameter applications, particularly where manufacturing constraints limit design options. This study investigates the applicability of conventional flux-barrier design principles in a SynRM with a 25.24-mm rotor diameter and evaluates alternative rotor configurations. A comparative analysis was conducted between two conventionally parameterized flux-barrier designs, an innovative segmented rotor topology, and a theoretical three-barrier design. Finite element analysis revealed that the segmented rotor achieves superior performance with a saliency ratio of 2.07 and torque density of 2.2 × 10⁻5 N·m/mm3, comparable to larger machines reported in recent literature. At 5000 r/min and 50A, this configuration delivers 0.78 N·m torque with 45.75

This paper focuses on the control of an n-port Multi-Active Bridge, providing insights into switching sequences, a time-domain model, and an optimization algorithm concerning conduction and switching losses. Central to this analysis is the introduction of a novel concept known as winding voltage sequences, which encapsulate the switching sequences employed by the converter bridges. The algorithm proposed in this article aims to derive analytical expressions for the currents flowing through all transformer windings (and switches) for each switching sequence. This control methodology is characterized by a set of parameters—inter-leg and inter-bridge phase shifts—whose diverse values are systematically explored to attain an optimal solution.

This paper proposes a control optimization of a Quadruple Active Bridge (QAB) converter using a neural network. The QAB is a four-port converter capable of handling DC sources and loads at different voltages. Its central node is a transformer, which provides galvanic isolation between the ports. It will be shown that for a common switching frequency, there are seven degrees of freedom, making its optimal control particularly complex. This paper proposes a novel neural network-based approach to develop a controller which improves the performance on the basis of a non-simplified model of the transformer. The introduced optimization leads to significantly reduce conduction losses, enabling the converter to operate efficiently with variable voltages and powers over its entire operating range. The results are verified by simulation.

High-power electrical coils used in the electricity transmission network can create a noise nuisance for local residents. These industrial coils are made up of a multi-strand cable winding, giving them a cylindrical shell shape. Electromagnetic excitation by Lorentz forces induces coil vibration, creating an undesirable sound field. In this study, we investigate analytically and by numerical simulation the reduction of acoustic radiation using regularly spaced apertures. As the shell becomes porous (with a porosity of less than 10%), acoustic short-circuits appear. We show a reduction in radiation efficiency and the impact of apertures on the structure vibration. Our results offer insights into the design and optimization of apertured electrical coils to mitigate noise generation.

Purpose The purpose of this paper is to propose a new method that allows to compare the magnetic pressures of different pulse width modulation (PWM) strategies in a fast and efficient way. Design/methodology/approach The voltage harmonics are determined using the double Fourier integral. As for current harmonics and waveforms, a new generic model based on the Park transformation and a dq model of the machine was established taking saturation into consideration. The obtained analytical waveforms are then injected into a finite element software to compute magnetic pressures using nodal forces. Findings The overall proposed method allows to accelerate the calculations and the comparison of different PWM strategies and operating points as an analytical model is used to generate current waveforms. Originality/value While the analytical expressions of voltage harmonics are already provided in the literature for the space vector pulse width modulation, they had to be calculated for the discontinuous pulse width modulation. In this paper, the obtained expressions are provided. For current harmonics, different models based on a linear and a nonlinear model of the machine are presented in the referenced papers; however, these models are not generic and are limited to the second range of harmonics (two times the switching frequency). A new generic model is then established and used in this paper after being validated experimentally. And finally, the direct injection of analytical current waveforms in a finite element software to perform any magnetic computation is very efficient.

Electric machines are often perceived as silent, yet the noise they produce has become a significant issue. This paper presents a focused approach to understanding the source of this noise, aiming to enhance machine design. Our study centers on the vibratory model of a permanent magnet synchronous electric machine. The stator and rotor components (shaft, laminations, magnets, and flexible bearings) are modeled using finite element analysis. We calculate the magnetic forces from Maxwell's pressures, which are analytically determined using the subdomain method. A key aspect of our study is the consideration of dynamic eccentricity. The paper explores how the vibratory responses of the rotor affect theses stress and how to address the complexity of magneto-mechanical coupling. Our findings reveal that the magneto-mechanical coupling of the rotor directly and significantly impacts Maxwell's pressures, and has to be taken into account to characterize the dynamics of rotor and stator.

For electric vehicle motors, it is essential to control the sources of loss which could reduce the overall efficiency of the system. In this context, this article aims to present a detailed comparison of machine and inverter losses between the space vector pulse width modulation (SVPWM) and the discontinuous pulse width modulation 2 (DPWM2). To compare both PWM strategies on the WLTC (worldwide harmonized light vehicles test cycles) cycle in an efficient way, a full analytical model is used to predict inverter losses and a sequential use of an analytical and a finite element analysis is used to perform an in-depth analysis of machine losses. This semianalytical method which can be used for any pulse width modulation (PWM) strategy allows to speed up the calculations and the comparison of different PWM schemes. Experiments were then conducted for different operating points and supply voltage levels to validate the results. The theoretical and experimental results show that although the DPWM2 allows to reduce inverter losses, it still generates more machine losses compared to the SVPWM especially on the WLTC cycle, which makes the DPWM2 less efficient. Nevertheless, depending on the total supply voltage, the DPWM2 could be more or less interesting on the WLTC cycle with comparison with the SVPWM.

Vibrational energy harvesting on electric machines can be used to power health monitoring sensors for these machines. This study investigates the energy harvesting from the vibrations of an induction machine, focusing on frequency content. Vibrations of a Pulse Width Modulation (PWM)-fed induction machine are analyzed: the study of the frequency spectrum of the PWM supply allows prediction of frequency content of the surface vibration of the stator. These stator vibrations are converted into voltage by an amplified resonant piezoelectric stack mechanical energy harvester. Furthermore, the resonances of the motor and the harvester are exploited to increase the level of voltage generated on a resistive load. These resonances are excited by vibration lines in frequency spectrum caused by the PWM supply, that we control and explain with the switching frequency.

The magnetic pressure generated in the stator of electric machines can be a significant source of noise and vibration. The vibration behavior of the stator and such mechanical structures primarily depends on their geometry. Although the stator is often considered a simple structure, its teeth are not included in this assumption. In this paper, we endeavor to evaluate the impact of stator geometrical variability on the vibration behavior of electric machines. Our sensitivity study reveals that natural frequencies and frequency response functions are highly sensitive to geometrical variability. To account for this, we conducted a variability propagation study using a stochastic finite element model. Our findings show negligible variability on the natural frequencies but a high variability on the frequency response functions, even with low input variability. As anticipated, our study highlights the critical role of accounting for geometrical variability to enhance the accuracy of finite element models and strengthen their predictive power. However, the main contribution of this work is that the vibration behavior of the stator is not coupled, implying that the impact on natural frequencies does not necessarily reflect the same effect on the frequency response function.

— this paper aims to present the relation between acoustic noise and torque ripple. An equation evaluating the variation of acoustic noise caused by reducing torque ripple in synchronous reluctance machine (SynRM) is proposed. First, qualitative relation between the torque and the radial magnetic pressure (RMP) is presented. A quantitative relation between the RMP and torque is defined. Thirdly, based on the proposed equation, the influence of torque ripple reduction on electromagnetic noise is studied. The evaluation method is also computed thanks to the vibro-acoustic software Manatee. It can be concluded that the proposed approach can analyze effect of reducing torque ripple on acoustic noise.

This paper presents a lumped-parameter thermal network (LPTN) model construction of a synchronous reluctance machine (SynRM) with segmented rotor and its validation. The 180W machine is intended to actuate an automotive clutch thus, installed in an ambient temperature up to 140◦C. In such machine, to make sure that a precise prediction of the temperature inside the machine can be achieved, deduction of thermal resistance of anisotropic component, surface contact, and external casing convection need particular attention. The external casing convection has been experimentally identified. The contact resistance between components were computed using effective airgap. The method used to compute thermal resistances of anisotropic component and surface contact are explained. The identification method used to deduce the thermal resistance of external surface is also presented. Finally, a validation experiments at different operating points of copper losses have shown that the 3D LPTN model is precise and robust with a maximum error of less than 3% at both transient and steady state.

Synchronous reluctance machine (SynRM) has been studied widely in order to reduce its high torque ripple and improve its low power factor. This article proposes a torque ripple reduction method for SynRM by defining a novel parameter-torque function. With the help of torque function, the optimal currents aiming to compensate torque harmonics are obtained. The advantage of the proposed method is that torque function can be obtained easily and torque ripple reduction can be achieved by a simple control method. For the purpose of verifying the proposed method, both simulations and experiments are performed. Finally, the influence of power supply and parameter uncertainty on the proposed method has also been discussed.