A method is proposed in this article to study the effect of particle size distribution on eddy-current loss from the microstructure model of soft magnetic composite (SMC). Unlike the previous ones, the microstructural model in this article is constructed based on the simulation data of the powder densification process. The simulation process uses the discrete element method (DEM), and the construction process is completed by the proposed 3-D reconstruction program. The generated model is analyzed by the finite element method (FEM) to investigate the differences between the eddy-current loss of SMCs with multiple particle size distributions. The analysis separates the eddy-current loss into intra-particle and inter-particle ones at the microscopic level, and an equation applicable to the calculation of eddy-current loss is proposed accordingly. For the eddy-current loss inside the particles, when the frequency increases so that the skin depth is smaller than the average particle size, the loss is no longer the square of the frequency. The experimental results show that the equation can accurately calculate the eddy-current loss under different particle size distributions. Moreover, the degree of intermetallic insulation of the particles plays a crucial role in regulating the eddy-current loss, especially for smaller particle-size SMCs.

Effect of Particles Size on Eddy-Current Loss of Soft Magnetic Composites Using Combined DEM and FEM

Cores for electromagnetic applications made of Soft Magnetic Composite (SMC) materials consist of
individually electrically insulated magnetic iron particles, processed by conventional powder metallurgy
(PM) routes. The core loss characteristics of a finalized SMC component are related to the process
treatments that it has been subjected to. In this context, the effect of uniaxial compaction and
annealing steps has been assessed for different pressure and temperature regimes by means of
electron backscatter diffraction (EBSD) and nano-indentation techniques. Deformation maps obtained
with EBSD were coupled with nano-mechanical testing, denoting the degree of induced stresses and
their relaxation in the cross sections of the parts. The development of the internal microstructure and
extent of mechanical deformation under processing were also evaluated and correlated to the
performance of the parts under question. The results reveal a more direct approach for determining
the relationship between magnetic properties and processing treatment of SMC components.

Assessment of the compacting and annealing process steps on the performance of finished Soft Magnetic Composite components

Robust multi-objective transverse flux machine drive optimization considering torque ripple and manufacturing uncertainties

Soft magnetic composite (SMC) material has been fabricated using 9 different powder particle fractions (smallest fraction: 400 μm). The microstructure features and resulting magnetic properties have been quantified and correlated. A specific focus lies on simultaneous consideration of the effects of particle size and internal grain size. Analysis has been carried out on samples in green condition and samples annealed between 400 °C and 600 °C. Electron backscatter diffraction technology brings about a substantially additional value to characterize deformations inside the grains. By detailed advanced microstructure analysis, it is shown that the deformation and recrystallization behavior is significantly different for different particle sizes used. Particle sizes between 100 and 200 μm show grain size distributions with the largest grains (d50 ~ 44 μm) in the volume of the particles resulting in the lowest hysteresis losses (PH ~ 4 W/kg, 1 T, 50 Hz). The relationship between particle and internal grain size distribution has been analyzed to enable further improvement of SMC materials concerning hysteresis loss reduction.

Tailoring the Microstructure of Soft Magnetic Composites for Electric Motor Applications

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

S. Schweizer

Author Tools

Chat about Author

Papers

Tailoring the Microstructure of Soft Magnetic Composites for Electric Motor Applications