At last year's edition of EVS, we presented an improved model for iron losses prediction in Permanent Magnet Synchronous Machines (PMSM) [1]. The benefit of this model holds in that it fits more closely the real material behavior than the standard Steinmetz or Bertotti approaches [2], by including 1) magnetic material characteristics measured at high frequency and 2) an improved representation of iron losses at the approach to saturation (by introducing a higher order term in J). We are taking this model a step further by considering now another phenomenon impacting iron losses in electrical machines: the decrease of magnetic permeability and the increase of local hysteresis loss at the vicinity of lamination edges due to the cutting process. This paper presents a quantitative analysis of the impact of lamination processing (cutting, punching, etc) for high quality low loss electrical steels used in automotive traction applications. It is important to perform the analysis over a wide frequency range, because of the large speed range of PMSM drives in automotive applications and the presence of higher harmonics (PWM supply). Our approach consists in measuring the material characteristics for sample sets with different ratios of degraded vs. non degraded material and at various frequencies. Starting from that experimental data we propose a method to determine the local magnetization curves, as function of distance from the cut edge. These local material characteristics can then be implemented in a FE model so that the effect of punching on the machine performance can be determined quantitatively: (1) the cutting impact on magnetization modification allows more precise field calculations; (2) a proposition is made on the implementation of the cutting impact on the loss calculations in post processing via an enhanced version of the loss model developed in [1].
The goal of this paper is to investigate the accuracy of modeling the excess loss in electrical steels using a time domain model with Bertotti's loss model parameters n 0 and V 0 fitted in the frequency domain. Three variants of iron loss models based on Bertotti's theory are compared for the prediction of iron losses under sinusoidal and non-sinusoidal flux conditions. The non-sinusoidal waveforms are based on the realistic time variation of the magnetic induction in the stator core of an electrical machine, obtained from a finite element-based machine model.
Within the market evolution towards higher efficiency machines, there is a need for more precise modelling tools, taking also higher frequency power supplies into account. This paper implements the effect of cut edge degradation, due to punching, on the local magnetization curve and local losses, aiming at improved calculation of magnetization current and machine iron losses. For an induction machine, defined by Leroy Somer and a high efficiency electrical steel, selected from ArcelorMittal's range, this study combines advanced material characterization with improved modelling techniques, and is validated by selected machine testing procedures. For the sake of clear loss separation a machine with slotless rotor was characterized at two conditions regarding speed and excitation. The loss model, including already the effect of rotational losses and higher harmonics, was enhanced with the punching effect, which led to a model accuracy of 86% at synchronous speed when compared to the measured losses. This study also led to further insights in local magnetization behaviour, to be used in further design optimization.
Cutting leads to a certain local magnetic material degradation of the electrical steel sheet. Moreover, the material properties near the cutting edge contribute significantly to the global performance. This material degradation mostly occurs in the vicinity of critical parts of electromagnetic devices, such as stator and rotor teeth. Therefore, the need exists to characterize the local magnetic hysteresis properties due to cutting. We couple the non destructive measurements of needle signals, which are dependent on the local variations in magnetic hysteresis properties, with a numerical inverse algorithm. The inverse algorithm interprets the needle signals so that the unknown magnetic hysteresis properties can be reconstructed. The paper mainly deals with the construction of an accurate material model (numerical forward model), the correct solution of the inverse procedure and the validation of the obtained results. We reconstructed local magnetic hysteresis properties of differently cut steel sheets and we observed that it is possible to recover the material characteristics using a material model, which fully characterizes the hysteresis properties.
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