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Title: Prediction of the effect of building factors on the magnetic performance of electrical steels in automotive applications
Author: Lewis, Nicholas James
ISNI:       0000 0004 7223 6063
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2017
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Electrical steel is the predominant material used for the magnetic cores of electrical machines, such as the rotors and stators of electric motors. The cutting of electrical steel during the motor manufacturing process is detrimental to the magnetic properties and consequently the properties in operation will be different from those measured, on strips, by the steel manufacturer. The ability to predict the effect of the manufacturing processes on the magnetic performance would be of great benefit to the electrical machine designer. An enhanced system was developed to measure the local magnetic properties with the addition of being able to accurately map the properties of complex geometries in a time efficient manner. The local magnetic properties of 0.35 mm thick 2.4 % and 3.2 % silicon, punched non-oriented electrical steel rings with constant outer diameter and varying inner diameter were measured to explore and predict the effect of punching. The distinct contrast in flux density profile between the grades was attributed to spreading of residual stress from punching. The 3.2 % Si samples showed a degradation depth consistent between ring widths and extending 2.5 ± 0.5 mm from the edge, while the 2.4 % Si samples displayed a more gradual decrease. Original models were proposed to predict the increase in power loss and the flux density profile based on the residual stress distribution. This novel modelling approach, validated using FEM software, could accurately reproduce the flux density profile and showed good agreement with experimental results, within 5% for most data points. The integration of this four-parameter model into FEM packages could greatly aid the designers of EMs by improving the ability to accurately predict the flux density throughout a motor core, ultimately improving the efficiency of these machines.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available