Inclusion of hysteresis and eddy current losses in dynamic induction machine models

2011 IEEE International Electric Machines &Amp; Drives Conference (IEMDC)

et al. 2011

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Abstract-The paper applies a dynamic space-vector model to loss-minimizing control in induction motor drives. The induction motor model, which takes hysteresis losses and eddy-current losses as well as the magnetic saturation into account, improves the flux estimation and rotor-flux-oriented control. Based on the corresponding steady-state loss function, a method is proposed for solving the loss-minimizing flux reference at each sampling period. A flux controller augmented with a voltage feedback algorithm is applied for improving the dynamic operation and field weakening. Both the steady-state and dynamic performance of the proposed method is investigated using laboratory experiments with a 2.2-kW induction motor drive. The method improves the accuracy of the loss minimization and torque production, it does not require excessive computational resources, and it shows fast convergence to the optimum flux level.

Section: A Flux Observer With Core-loss Compensationmentioning

confidence: 99%

“…No-load tests were performed to obtain the parameters used in the stator-inductance function (5) and in the core-loss conductance function (8). The stator voltage (5) were obtained by minimizing…”

Section: B Parameter Identificationmentioning

confidence: 99%

Loss-minimizing flux level control of induction motor drives

Ranta

2011 IEEE International Electric Machines &Amp; Drives Conference (IEMDC)

et al. 2011

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“…An often used way to model the saturation of the induction motor is to model the stator inductance as a function of the stator flux, e.g. [10]. Furthermore, the low-power induction motors are often equipped with closed rotor slots, making the rotor leakage flux saturate highly as a function of rotor current (i.e., torque) [11].…”

Section: Introductionmentioning

confidence: 99%

Influence of Magnetic Saturation on Modeling of an Induction Motor

Mölsä

Saarakkala

2018 XIII International Conference on Electrical Machines (ICEM)

2018

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This paper deals with modeling of a saturated induction machine. In control algorithms, the inverse-Γ model is widely used. However, the saturation models are typically based on the T or Γ model. Transformation between these models is easy if the machine is magnetically linear, but since the motor saturates, the modeling becomes more complex. In this paper, we study the properties of the Γ and inverse-Γ models and the transformation between these two models when the saturation is taken into account. The phenomena related to model transformation are studied by means of analytical equations. Also, the functionality of the models is studied by means of laboratory experiments.

“…The hysteresis losses and the eddy-current losses are included in the model, but, in principle, any kind of core-loss profile could be applied. A similar approach is used in [7] for the case of stator core loss modelling in induction machines. The model can easily be tuned and implemented in different applications.…”

Section: Introductionmentioning

confidence: 99%

Inclusion of hysteresis and eddy current losses in nonlinear time-domain inductance models

Ranta

IECON 2011 - 37th Annual Conference of the IEEE Industrial Electronics Society

Belahcen

et al. 2011

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Abstract-A time-domain model including the core losses of a nonlinear inductor is proposed. The model can be seen as a parallel combination of a nonlinear inductance modelling the saturation and a nonlinear resistance modelling the core losses. The desired steady-state core-loss profile is used to determine the resistance function. The model is easy to implement and can be used in many different applications. The hysteresis loop of an electrical steel sample is measured at several frequencies in order to experimentally verify the model. It is shown that the model is able to predict both major and minor hysteresis loops very well. I. INTRODUCTIONModelling of nonlinear hysteretic inductances has challenged researchers for many years. A good accuracy can indeed be achieved by a physical in-depth analysis, but the resulting differential equations are very complicated. In, for instance, design and real-time control of electric drives and power electronic devices, dynamic time-domain models that are easy to implement and tune are desirable. The increasing demand for energy efficiency makes the need for accurate models of losses even larger in the future.The core losses can be divided into three parts: hysteresis losses, classical eddy current losses and excess losses. The hysteresis losses are proportional to the frequency, while the classical eddy current losses and the excess losses are proportional to the frequency raised to the second and 1.5th power, respectively.A generally used and very simple model of the core losses of an inductance is a constant resistance in parallel to the inductance. In the case of a sinusoidal waveform, the power dissipated in a constant resistor is proportional to the square of the frequency. This frequency dependency corresponds to the classical eddy current losses. Particularly at lower frequencies, the hysteresis losses constitute a significant part of the total core losses, and the losses predicted by a constant resistance deviate remarkably from the actual losses.Several methods have been developed to achieve more accurate models. A general framework for modelling of hysteresis utilizing a dissipating function and a restoring function was presented in [1], [2], but no explicit function was given. In [3] a polynomial function was used to model the hysteresis loop assuming sinusoidal voltage excitation. A polynomial model for the B-H relation using the concept of a hysteresis related field intensity was proposed in [4]. In [5], a system of differential equations was developed based on the idea of separating the magnetic field into two parts, where one part