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http://hdl.handle.net/10985/9861
Characterization of the local Electrical Properties of Electrical Machine Parts with non-Trivial Geometry
ARBENZ, Laure; BENABOU, Abdelkader; CLENET, Stéphane; MIPO, Jean-Claude; FAVEROLLE, Pierre
In electrical machines, knowing the electrical conductivity is of importance for the eddy current calculation, especially when massive iron parts are involved. Generally the conductivity is measured on samples of raw materials with simple geometries. Indeed, a simple geometry is suitable for applying an analytical approach to deduce the electrical conductivity from the measured electrical quantities. Nevertheless, when a non destructive measurement is required, the measurement of the electrical conductivity can become rather difficult on parts with complex geometry. To that end, with the help of the Finite Element Modeling approach (FEM), a strategy is developed to characterize the local electrical properties of parts with a non-trivial geometry.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/98612015-01-01T00:00:00ZARBENZ, LaureBENABOU, AbdelkaderCLENET, StéphaneMIPO, Jean-ClaudeFAVEROLLE, PierreIn electrical machines, knowing the electrical conductivity is of importance for the eddy current calculation, especially when massive iron parts are involved. Generally the conductivity is measured on samples of raw materials with simple geometries. Indeed, a simple geometry is suitable for applying an analytical approach to deduce the electrical conductivity from the measured electrical quantities. Nevertheless, when a non destructive measurement is required, the measurement of the electrical conductivity can become rather difficult on parts with complex geometry. To that end, with the help of the Finite Element Modeling approach (FEM), a strategy is developed to characterize the local electrical properties of parts with a non-trivial geometry.Stochastic Jiles-Atherton model accounting for soft magnetic material properties variability
http://hdl.handle.net/10985/7296
Stochastic Jiles-Atherton model accounting for soft magnetic material properties variability
RAMAROTAFIKA, Rindra; BENABOU, Abdelkader; CLENET, Stéphane
Industrial processing (cutting, assembly…) of steel laminations can lead to significant modifications in their magnetic properties. Moreover, the repeatability of these modifications is not usually verified because of the tool wear or, more intrinsically, to the manufacturing process itself. When investigating the iron losses, it is generally observed that the hysteresis losses contribution are more likely to be affected. In the present work, twenty eight (28) samples of slinky stator (SS) are investigated, at a frequency of 5Hz and 1.5T. A stochastic model is then developed, using the Jiles-Atherton model together with a statistical approach to account for the variability of the hysteresis loops of the considered samples.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/72962013-01-01T00:00:00ZRAMAROTAFIKA, RindraBENABOU, AbdelkaderCLENET, StéphaneIndustrial processing (cutting, assembly…) of steel laminations can lead to significant modifications in their magnetic properties. Moreover, the repeatability of these modifications is not usually verified because of the tool wear or, more intrinsically, to the manufacturing process itself. When investigating the iron losses, it is generally observed that the hysteresis losses contribution are more likely to be affected. In the present work, twenty eight (28) samples of slinky stator (SS) are investigated, at a frequency of 5Hz and 1.5T. A stochastic model is then developed, using the Jiles-Atherton model together with a statistical approach to account for the variability of the hysteresis loops of the considered samples.Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines
http://hdl.handle.net/10985/7075
Stochastic Modeling of Soft Magnetic Properties of Electrical Steels: Application to Stators of Electrical Machines
RAMAROTAFIKA, Rindra; BENABOU, Abdelkader; CLENET, Stéphane
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
La version éditeur de cet article est disponible à l'adresse suivante : 10.1109/TMAG.2012.2201734
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/70752012-01-01T00:00:00ZRAMAROTAFIKA, RindraBENABOU, AbdelkaderCLENET, StéphaneTo 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 samplesModelling of a hysteresis motor using the Jiles-Atherton model
http://hdl.handle.net/10985/10139
Modelling of a hysteresis motor using the Jiles-Atherton model
BENABOU, Abdelkader; CLENET, Stéphane; BOUAZIZ, Lounas
In this paper, we present a model of a hysteresis motor based on Maxwell's equations coupled with the Jiles-Atherton (J-A) hysteresis model solved by the finite element method. The aim of this work is to validate such a model by comparison with the experimental results (electromagnetic torque, voltage, current). We also present an analysis of this motor when imposing current or voltage in the 2D vector potential formulation.
Thu, 01 Jan 2015 00:00:00 GMThttp://hdl.handle.net/10985/101392015-01-01T00:00:00ZBENABOU, AbdelkaderCLENET, StéphaneBOUAZIZ, LounasIn this paper, we present a model of a hysteresis motor based on Maxwell's equations coupled with the Jiles-Atherton (J-A) hysteresis model solved by the finite element method. The aim of this work is to validate such a model by comparison with the experimental results (electromagnetic torque, voltage, current). We also present an analysis of this motor when imposing current or voltage in the 2D vector potential formulation.Non Linear Proper Generalized Decomposition method applied to the magnetic simulation of a SMC microstructure
http://hdl.handle.net/10985/7815
Non Linear Proper Generalized Decomposition method applied to the magnetic simulation of a SMC microstructure
HENNERON, Thomas; BENABOU, Abdelkader; CLENET, Stéphane
Improvement of the magnetic performances of Soft Magnetic Composites (SMC) materials requires to link the microstructures to the macroscopic magnetic behavior law. This can be achieved with the FE method using the geometry reconstruction from images of the microstructure. Nevertheless, it can lead to large computational times. In that context, the Proper Generalized Decomposition (PGD), that is an approximation method originally developed in mechanics, and based on a finite sum of separable functions, can be of interest in our case. In this work, we propose to apply the PGD method to the SMC microstructure magnetic simulation. A non-linear magnetostatic problem with the scalar potential formulation is then solved.
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/78152012-01-01T00:00:00ZHENNERON, ThomasBENABOU, AbdelkaderCLENET, StéphaneImprovement of the magnetic performances of Soft Magnetic Composites (SMC) materials requires to link the microstructures to the macroscopic magnetic behavior law. This can be achieved with the FE method using the geometry reconstruction from images of the microstructure. Nevertheless, it can lead to large computational times. In that context, the Proper Generalized Decomposition (PGD), that is an approximation method originally developed in mechanics, and based on a finite sum of separable functions, can be of interest in our case. In this work, we propose to apply the PGD method to the SMC microstructure magnetic simulation. A non-linear magnetostatic problem with the scalar potential formulation is then solved.Stochastic post-processing calculation of iron losses – application to a PMSM
http://hdl.handle.net/10985/7255
Stochastic post-processing calculation of iron losses – application to a PMSM
FRATILA, Mircea; RAMAROTAFIKA, Rindra; BENABOU, Abdelkader; CLENET, Stéphane; TOUNZI, Abdelmounaïm
To take account of the uncertainties introduced on the magnetic properties during the manufacturing process, the present work aims to focus on the stochastic modelling of iron losses in electrical machine stators. The investigated samples are composed of 28 slinky stators, coming from the same production chain. The stochastic modelling approach is first described. Thereafter, the Monte-Carlo sampling method is used to calculate, in post-processing, the iron loss density in a PMSM that is modelled by the finite element method. The interest of such an approach is emphasized by calculating the main statistical characteristics associated to the losses variability, which are Gaussian distributed for A and O formulations. The originality of the approach is due to the fact that the global influence of the manufacturing process (cutting, assembly, …) on magnetic properties of the considered samples is taken into account in the way of computing the iron losses.
Tue, 01 Jan 2013 00:00:00 GMThttp://hdl.handle.net/10985/72552013-01-01T00:00:00ZFRATILA, MirceaRAMAROTAFIKA, RindraBENABOU, AbdelkaderCLENET, StéphaneTOUNZI, AbdelmounaïmTo take account of the uncertainties introduced on the magnetic properties during the manufacturing process, the present work aims to focus on the stochastic modelling of iron losses in electrical machine stators. The investigated samples are composed of 28 slinky stators, coming from the same production chain. The stochastic modelling approach is first described. Thereafter, the Monte-Carlo sampling method is used to calculate, in post-processing, the iron loss density in a PMSM that is modelled by the finite element method. The interest of such an approach is emphasized by calculating the main statistical characteristics associated to the losses variability, which are Gaussian distributed for A and O formulations. The originality of the approach is due to the fact that the global influence of the manufacturing process (cutting, assembly, …) on magnetic properties of the considered samples is taken into account in the way of computing the iron losses.Experimental characterization of the iron losses variability in stators of electrical machines
http://hdl.handle.net/10985/7115
Experimental characterization of the iron losses variability in stators of electrical machines
RAMAROTAFIKA, Rindra; BENABOU, Abdelkader; MIPO, Jean-Claude; CLENET, Stéphane
Manufacturing processes may introduce a significant variability on the magnetic properties of claw pole generator stators. The present work deals with the analysis of two groups of stator samples. The first group is composed of 28 slinky stators (SS) and the second group is composed of 5 stators, manufactured using laser cut stacked laminations (SL). Both groups are made from the same lamination grade and with the same geometrical dimensions. Characterization was carried out for several levels of excitation field at 50Hz. A noticeable variability has been observed on the iron losses for SS samples, whereas it appears to be not significant for SL samples. The loss separation technique has then been investigated for the SS samples. Results show that the variability of static losses is more important than the one of dynamic losses.
Version éditeur disponible à l'adresse suivante : http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6172417
Sun, 01 Jan 2012 00:00:00 GMThttp://hdl.handle.net/10985/71152012-01-01T00:00:00ZRAMAROTAFIKA, RindraBENABOU, AbdelkaderMIPO, Jean-ClaudeCLENET, StéphaneManufacturing processes may introduce a significant variability on the magnetic properties of claw pole generator stators. The present work deals with the analysis of two groups of stator samples. The first group is composed of 28 slinky stators (SS) and the second group is composed of 5 stators, manufactured using laser cut stacked laminations (SL). Both groups are made from the same lamination grade and with the same geometrical dimensions. Characterization was carried out for several levels of excitation field at 50Hz. A noticeable variability has been observed on the iron losses for SS samples, whereas it appears to be not significant for SL samples. The loss separation technique has then been investigated for the SS samples. Results show that the variability of static losses is more important than the one of dynamic losses.Temperature Dependence in the Jiles–Atherton Model for Non-Oriented Electrical Steels: An Engineering Approach
http://hdl.handle.net/10985/13419
Temperature Dependence in the Jiles–Atherton Model for Non-Oriented Electrical Steels: An Engineering Approach
HUSSAIN, Sajid; BENABOU, Abdelkader; CLENET, Stéphane; LOWTHER, David A.
High operating temperatures modify the magnetic behavior of ferromagnetic cores which may affect the performance of electrical machines. Therefore, a temperature-dependent material model is necessary to model the electrical machine behavior more accurately during the design process. Physics-inspired hysteresis models, such as the Jiles–Atherton (JA) model, seem to be promising candidates to incorporate temperature effects and can be embedded in finite element simulations. In this paper, we have identified the JA model parameters from measurements for a temperature range experienced by non oriented electrical steels in electrical machines during their operation. Based on the analysis, a parameter reduction has been performed. The proposed approach simplifies the identification procedures by reducing the number of model parameters and does not require any additional material information, such as the Curie temperature. The resulting temperature-dependent JA model is validated against measurements, and the results are in good agreement.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/134192018-01-01T00:00:00ZHUSSAIN, SajidBENABOU, AbdelkaderCLENET, StéphaneLOWTHER, David A.High operating temperatures modify the magnetic behavior of ferromagnetic cores which may affect the performance of electrical machines. Therefore, a temperature-dependent material model is necessary to model the electrical machine behavior more accurately during the design process. Physics-inspired hysteresis models, such as the Jiles–Atherton (JA) model, seem to be promising candidates to incorporate temperature effects and can be embedded in finite element simulations. In this paper, we have identified the JA model parameters from measurements for a temperature range experienced by non oriented electrical steels in electrical machines during their operation. Based on the analysis, a parameter reduction has been performed. The proposed approach simplifies the identification procedures by reducing the number of model parameters and does not require any additional material information, such as the Curie temperature. The resulting temperature-dependent JA model is validated against measurements, and the results are in good agreement.Characterization of the local incremental permeability of a ferromagnetic plate based on a four needles technique
http://hdl.handle.net/10985/11754
Characterization of the local incremental permeability of a ferromagnetic plate based on a four needles technique
ARBENZ, Laure; BENABOU, Abdelkader; CLÉNET, Stéphane; FAVEROLLE, Pierre; MIPO, Jean-Claude
The performances of electrical machines depend highly on the behavior of ferromagnetic materials. In some applications, these materials operate under DC polarization, i.e. when the magnetic field oscillates around a DC bias. In that condition, it is required to know the incremental permeability which characterizes the magnetic behavior of the material around the operating point. In this paper, a non-destructive approach, involving a combination of experiment and Finite Element (FE) technique, is presented in order to determine the incremental permeability. The proposed sensor is based on the four-needles method. With this sensor, Bowler et al. have proposed a method to determine the initial permeability of homogeneous metal plates based on an analytical model. Here we propose to use the same kind of sensor to determine the incremental permeability. The measurement process is analyzed using a FE model. It is shown that the analytical approach reaches its limits if the permeability of the plate and its thickness become too high. A combination between the measurements and a FE model is introduced to overcome this
Fri, 01 Jan 2016 00:00:00 GMThttp://hdl.handle.net/10985/117542016-01-01T00:00:00ZARBENZ, LaureBENABOU, AbdelkaderCLÉNET, StéphaneFAVEROLLE, PierreMIPO, Jean-ClaudeThe performances of electrical machines depend highly on the behavior of ferromagnetic materials. In some applications, these materials operate under DC polarization, i.e. when the magnetic field oscillates around a DC bias. In that condition, it is required to know the incremental permeability which characterizes the magnetic behavior of the material around the operating point. In this paper, a non-destructive approach, involving a combination of experiment and Finite Element (FE) technique, is presented in order to determine the incremental permeability. The proposed sensor is based on the four-needles method. With this sensor, Bowler et al. have proposed a method to determine the initial permeability of homogeneous metal plates based on an analytical model. Here we propose to use the same kind of sensor to determine the incremental permeability. The measurement process is analyzed using a FE model. It is shown that the analytical approach reaches its limits if the permeability of the plate and its thickness become too high. A combination between the measurements and a FE model is introduced to overcome thisCharacterization of massive magnetic parts with a dedicated device
http://hdl.handle.net/10985/16759
Characterization of massive magnetic parts with a dedicated device
BORSENBERGER, Marc; BENABOU, Abdelkader; BAUDOUIN, Cyrille; BIGOT, Régis; FAVEROLLE, Pierre; MIPO, Jean-Claude
Magnetic parts are usually composed of a stack of electrical steel laminations to reduce the eddy current losses. However, for cost reasons or for specific applications the magnetic core can be made from massive steel and thus manufactured with adapted processes such as forging. Such process may lead to inhomogeneous and degraded magnetic properties. Therefore, this study proposes a specific device for characterizing magnetic properties of samples which are to be representative of a massive part. The measure is based on the Faraday’s equation to determine the magnetic flux density and the Hall effect to estimate the magnetic field inside the sample. Practically this is realized with classical components such as Hall probes, a secondary winding and an electromagnet device. However their combination is unique to perform magnetic characterization on massive samples, which are less affected by the sampling technique and may have anisotropic properties. The device is dimensioned thanks to FE-Simulation and validated according repeatability, sensitivity and trueness analysis. Eventually the characterization is performed on samples with different material parameters showing the effect of the grain size on the specific losses. The expected effect of the grain flow on magnetic properties is however not proven yet.
Mon, 01 Jan 2018 00:00:00 GMThttp://hdl.handle.net/10985/167592018-01-01T00:00:00ZBORSENBERGER, MarcBENABOU, AbdelkaderBAUDOUIN, CyrilleBIGOT, RégisFAVEROLLE, PierreMIPO, Jean-ClaudeMagnetic parts are usually composed of a stack of electrical steel laminations to reduce the eddy current losses. However, for cost reasons or for specific applications the magnetic core can be made from massive steel and thus manufactured with adapted processes such as forging. Such process may lead to inhomogeneous and degraded magnetic properties. Therefore, this study proposes a specific device for characterizing magnetic properties of samples which are to be representative of a massive part. The measure is based on the Faraday’s equation to determine the magnetic flux density and the Hall effect to estimate the magnetic field inside the sample. Practically this is realized with classical components such as Hall probes, a secondary winding and an electromagnet device. However their combination is unique to perform magnetic characterization on massive samples, which are less affected by the sampling technique and may have anisotropic properties. The device is dimensioned thanks to FE-Simulation and validated according repeatability, sensitivity and trueness analysis. Eventually the characterization is performed on samples with different material parameters showing the effect of the grain size on the specific losses. The expected effect of the grain flow on magnetic properties is however not proven yet.