Punching influence on magnetic properties of the stator teeth of an induction motor

Kedous-Lebouc, A.; Cornut, B.; Perrier, J.; Manfé, Ph; Chevalier, Thierry

doi:10.1016/s0304-8853(02)00803-x

Cited by 35 publications

(22 citation statements)

References 2 publications

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“…However, such assumption reveals itself insufficient as the manufacturing of an electrical machine, from the cutting of laminations till the final magnetic core shape, requires several industrial processes that might significantly impact the magnetic properties. In fact, these processes may introduce some residual stresses that have an impact on the magnetic behavior law and iron losses of the considered material [30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines

2012

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To take account of the uncertainties introduced on the soft magnetic materials properties (magnetic behavior law, iron losses) during the manufacturing process, the present work deals with the stochastic modeling of the magnetic behavior law B-H and iron losses of claw pole stator generator. Twenty eight (28) samples of slinky stator (SS) coming from the same production chain have been investigated. The used approaches are similar to those used in mechanics. The accuracy of existing anhysteretic models has been tested first using cross validation techniques. The well known iron loss separation model has been implemented to take into account the variability of the losses. Then, the Multivariate Gaussian distribution is chosen to model the variability and dependencies between identified parameters, for both behavior law and iron loss models. The developed stochastic models allow predicting a 98% confidence interval for the considered samples.

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Section: Introductionmentioning

confidence: 99%

Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines

2012

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“…Nowadays it engineer to compute iron losses based on (1 terms equation started from Steinmetz [1 years later by a contribution of Jordan who components: static (hysteresis) and dynami losses. Bertotti improvement was the intr third term excess-anomalous losses [16]. k h loss coefficient) and k a (anomalous iron cannot be estimated analytically, both of strong dependence on magnetic flux densi and frequency) and material properties.…”

Section: Iron Loss Computatimentioning

confidence: 99%

“…All these computations are rou material is not perfect and the cutt the iron losses especially in the too be doubled [16]. eparation of iron losses in proach, trying to separate d magnetic flux density, cal phenomena directly.…”

Section: Iron Loss Computatimentioning

confidence: 99%

BLDC multiphase reluctance machines: A revival attempt with 2D FEM investigation and standstill tests

Agarlita

Ursu

Tutelea

et al. 2013

2013 IEEE Energy Conversion Congress and Exposition

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In an yet another effort to produce better PM-less rotor-winding-less, brushless electric motor drives, the present paper reports on preliminary work related to multiphase (m=6) high saliency rotor, dual-flat-top alternative current control BLDC reluctance machine drives. The aim is to produce high torque density, low loss / torque in a PM-less, rotor winding-less machine by full usage of machine windings and core and of inverter kVA. A new derivation of the principle of operation, essential rotary and linear machine topologies and a 2-D FEM analysis for torque density and torque pulsations on an already built (6 phase, 6 poles) -35Nm lab prototype are made available and show promising results. Experimental flux decay tests results are shown, which, together with standstill torque measurements, validate the FEM model. Machine geometry (Axially Laminated Anisotropic Rotor) and control (rectangular current waveform) can produce important core losses, but, as the paper will show (by advanced FEM computation) in our case they don't represent a problem. The BLDC-MRM control is dynamically simulated for the four quadrant operation, thus preparing the ground for running tests.

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“…Thus, the blanking process is still used for the rotor and stator plates manufacturing. Many studies are related with the analysis of the magnetic lossiness and magnetic disturbance in the sheets produced by various techniques [5,15,20,27,32]. Typical materials used for blanking tools are high-speed steels such as: M2, K945, M35, M42, ASP23, ASP30, ASP60 (ASP-Asea Stora Process).…”

Section: Introductionmentioning

confidence: 99%

The tool surface wear during the silicon steel sheets blanking process

Mucha¹,

Jaworski²

2016

EiN

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Punching influence on magnetic properties of the stator teeth of an induction motor

Cited by 35 publications

References 2 publications

Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines

Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines

BLDC multiphase reluctance machines: A revival attempt with 2D FEM investigation and standstill tests

The tool surface wear during the silicon steel sheets blanking process

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