A soft magnetic MnZn-type ferrite is considered for high frequency applications. First, the morphological, structural, and chemical composition of the material are presented and discussed. Subsequently, by using a vibrating sample magnetometer (VSM), the hysteresis loops are recorded. The open magnetic circuit measurements are corrected by employing demagnetization factors, and by taking into consideration the local magnetic susceptibility. Finally, the hysteresis losses are estimated by the Steinmetz approach, and the results are compared with available commercial information provided by selected MnZn ferrite manufacturers. Such materials are representative in planar inductor and transformer cores due to their typically low losses at high frequency, i.e., up to several MHz, in low-to-medium power applications and providing high efficiency of up to 97%–99%.

Soft magnetic materials are at the core of electromagnetic devices. Planar transformers are essential pieces of equipment working at high frequency. Usually, their magnetic core is made of various types of ferrites or iron-based alloys. An upcoming alternative might be the replacement the ferrites with FINEMET-type alloys, of nominal composition of Fe_73.5Si_13.5B₉Cu₃Nb₁ (at. %). FINEMET is a nanocrystalline material exhibiting excellent magnetic properties at high frequencies, a soft magnetic alloy that has been in the focus of interest in the last years thanks to its high saturation magnetization, high permeability, and low core loss. Here, we present and discuss the measured and modelled properties of this material. Owing to the limits of the experimental set-up, an estimate of the total magnetic losses within this magnetic material is made, for values greater than the measurement limits of the magnetic flux density and frequency, with reasonable results for potential applications of FINMET-type alloys and thin films in high frequency planar transformer cores.

Hysteresis phenomenon is currently met in magnetic materials characterization. From many years this hysteresis had been modeled with different approaches. The aim of this paper is to present a comparison between few sigmoid functions used more often in other research areas. The functions were updated according to the requirements of the magnetic hysteresis and there comparisons for three different magnetic materials were performed. In the last part, hysteresis losses are evaluated using relative errors between experimental loop area and modeled loop area.

In modern low-voltage electrical installations, the predictive maintenance of the major electrical equipments involved in the power delivery process (transformers) or in the conversion of the electrical energy (especially electric motors) becomes mandatory. Thus, a high level of reliability and safety is assured for both the electric facility and operators. The proactive maintenance is to be non-invasively performed and mainly requires an infrared (IR) thermographic inspection and power quality analysis of the installation loads. A vibration investigation is also necessary for the motor drive systems. The paper critically studies the first two main maintenance procedures revealing their main characteristics, performances and limits. A case-study presents a 1000 kVA distribution transformer that supplies a bakery facility that comprised mainly heaters and inductions motors as loads.

Nowadays, Failure Mode and Effect Analysis (FMEA) is more present in any standard evaluation of a product or process. In automotive industry, the IEC 61508 Standard adapted the ISO 26262 restrictions for Electrical and Electronic Devices. Conducting an FMEA reduces the costs by focusing on preventing failures, improving safety and increasing customer satisfaction. This paper presents a case study of a FMEA on a CAN (Controller Area Network) Bus Harness considering the entire process from defining the scope and building the team, to the action plan that will reduce the Risk Priority Number below the acceptable risk value. Also, the brainstorming that identifies the possible failure modes is presented.

The paper proposed an innovative predictive maintenance system, designated to monitor and diagnose critical electrical equipment (generally large power electric motors) within industrial electrical installations. A smart and minimally invasive system is designed and developed. Its scope is to evaluate continuously the essential operating parameters (electrical, thermal, and mechanical) of the investigated equipment. It manages to report the deviations of inspected machine operating parameters values from the rated ones. The system also suggests the potential cause of these abnormal variations along with possible means (if the defect is identified in a database, constantly updated with each appearance of a malfunction). The developed maintenance device generates an operating report of the analyzed equipment, in which the values of power quality and energy indicators are computed and interpreted. Additionally, real-time remote transmission of analyzed data is facilitated, making them accessible from any location. The proposed maintenance system is a low-cost device that is easy to install and use in comparison with similar existing devices and equipment. The designed maintenance system was tested on dedicated to low-voltage equipment up to 100 kW.