Accurate and simple magnetic material law is necessary to correctly model the complete electromagnetic systems. In this paper, a new formulation based on the scalar quasi-static hysteresis Jiles–Atherton model extended to dynamic behavior using fractional derivative dynamic contribution is proposed. The fractional contribution is solved using convolution which highly reduces the numerical issues. The order of the fractional derivation provides a new degree of freedom and allows obtaining correct simulation results on a very large frequency bandwidth. By using such a formulation, high-memory and time-consuming space discretization techniques (finite differences and finite elements) are avoided while keeping the global accurate simulation results.

This study aims to enhance the low-frequency induction heating (LFIH) effect in a thermoplastic polymer doped with iron oxide magnetic particles, which are promising candidates for several medical applications thanks to their confirmed biocompatibility. Two main approaches were proposed to successfully boost the heating ability; i.e., improving the magnetic concentration of the composite with higher filler content of 30 wt %, and doubling the frequency excitation after optimization of the inductor design. To test the magnetic properties of the ferromagnetic composite, a measurement of permeability as a function of temperature, frequency, and particle content was carried out. Thermal transfer based COMSOL simulations together with experimental tests have been performed, demonstrating feasibility of the proposed approach to significantly enhance the target temperature in a magnetic composite. These results are encouraging and confirmed that IH can be exploited in medical applications, especially for the treatment of varicose veins where local heating remains a true challenge.

Recycling ambient energies with electric generators instead of employing batteries with limited lifespans has motivated a large scientist community over two decades. Sea waves exhibit a large energy density. The amount of energy that could be extracted from the sea waves is very high. This work describes a technique of sea wave energy extraction based on a piezoelectric conversion and an analogy with thermodynamic Ericsson loops. By synchronizing external electric field to the maximum and the minimum of the sea wave mechanical stress excitations, the piezoelectric material dielectric hysteresis loop area is increased corresponding to the maximum of the energy available. In this article, technical solutions are proposed for the in site deployment of the proposed technique (maximum and minimum detection, external electric field source synchronization). Experimental measuring benches have been developed to monitor the sea wave mechanical excitation and to determine precisely the energy-harvesting potential. Adequate dielectric hysteresis model is proposed to numerically determine the best configuration (frequency, amplitude) of electric field to impose. Even if the Ericsson technique requires external electronic devices, the weak consumption of such components allows a large enhancement of the amount of energy extracted compared to a basic piezo element conversion.

Magnetic losses in a ferromagnetic lamination can be separated into three contributions. Bertotti theoretically assessed this distribution at the end of the 20th century in the Statistical Theory of Losses (STL), triggering significant progress in understanding the dissipation mechanisms. Recent studies have shown the possibility of reconstructing a hysteresis cycle from the high-frequency Barkhausen noise signal. Applying STL to the Barkhausen noise cycles has never been done before. Still, it could help establish a parallel with the measurement of the magnetization cycle versus frequency and the energy loss. However, STL analysis in its ultimate description requires sinusoidal flux density, while Barkhausen noise measurements are usually done with a constant excitation slope. Multiple magnetic flux density control methods were described in the literature and are reviewed in this manuscript. However, the Barkhausen noise context, requiring high-frequency sampling during the magnetization cycle, is more constraining. Therefore, specific performance criteria were considered, followed by numerical tests to determine the most adapted method to a Barkhausen STL description. Eventually, the Proportional Iterative Learning Control (P-ILC) gave the highest satisfaction rate and was chosen for experimental tests. Some of these experimental results are provided in the manuscript discussion together with suggestions for convergence speed improvement. It is, for instance, recommended to increase the gain near saturation, where the system response is poor.

Post-treatment and rescaling is made possible to plot local hysteresis cycles from the measurement of local magnetic Barkhausen noise (BN). If the material is homogeneous and if similar excitation conditions are imposed, the local hysteresis cycles obtained are comparable to the classical magnetic hysteresis cycles B(H) (the cross section magnetic average induction B as a function of the surface tangential excitation field H). These local BN hysteresis cycles provide interesting clues about the evolution of the microstructure of the magnetic material (internal stresses, level of degradation, etc.). This makes it an interesting tool for the non-destructive evaluation of ferromagnetic steels. In this paper, a phenomenological modeling of the BN from the local modeling of B subjected to an excitation field H and/or a uniaxial mechanical stress T is proposed. The final objective is to provide an absolute quantification of the internal residual stresses from the BN measurements.

Accurate and simple magnetic material behavior law is necessary to correctly model complete electromagnetic systems. In this paper, a new formulation based on the scalar quasi-static hysteresis Preisach model extended to dynamic behavior using fractional derivation dynamic contribution is proposed. The fractional contribution is solved using convolution which highly reduces the numerical issues. The order of the fractional derivation provides a new degree of freedom and allows to correctly obtain simulation results on a very large frequency bandwidth. By using such formulation, space discretization techniques (finite differences, finite elements) are avoided which are highly space and time consuming while keeping the global simulation results precise. The numerical implementation of the problem and some experimental validations are shown in this paper.