Classical Preisach Hysteresis Model Research Articles

Modeling and simulation of magnetostrictive actuators based on ΔE effect Preisach model

Based on the classical Preisach model, combined with the magneto-mechanical coupling effect of Giant magnetostrictive materials (GMM), this paper introduces the Everett function to optimize the classical Preisach hysteresis model and improve its accuracy. By importing dynamic parameters, the dynamic Preisach hysteresis model is established. Combined with the constitutive model of GMM, a dynamic Preisach hysteretic nonlinear magnetostrictive actuator model based on the ΔE effect is established. Then, the finite element simulation is carried out by Comsol software and compared with the theoretical model simulation. The results show that the error between the magnetostrictive strain of the established hysteresis model and the finite element simulation results is less than 100 ppm, which verifies the accuracy of the proposed model. Finally, the curves of magnetic field intensity, magnetic induction intensity, magnetization, magnetostrictive strain and ΔE effect of GMA are obtained by using this model.

Analytical Inverse Preisach Model and Its Comparison With Inverse Jiles–Atherton Model in Terms of Accuracy and Computational Speed

Inverse hysteresis model with magnetic flux density and magnetic field intensity as input and output respectively is more preferred, compared with the forward one, for resolving the electromagnetic issues of electrical equipment in terms of magnetic vector potential or with voltage sources. And an inverse hysteresis model with high accuracy and high computation speed both has broader range of applications. However, the well known classical Preisach hysteresis model is formulated with the forward form, and has the double integration of its distribution function, making it inconvenient and unpractical in the electrical engineering. In this paper, an analytical inverse Preisach model is proposed for the first time. Firstly, the analytical expressions of permeability of initial magnetization curve, descending and ascending branches of the hysteresis loop are derived using one closed form of Everett integral function. Subsequently the analytical inverse Preisach model is derived by the difference method, considering the reversible magnetization component that classical Preisach model cannot simulate with an odd function analytically. The experiment of one grain oriented silicon steel sample and one non-oriented silicon steel sample, under different magnetic excitation levels is conducted, and the accuracy and efficiency of the proposed analytical inverse Preisach model are confirmed by comparing its simulated hysteresis loops with the experimental ones and that computed with the widely used inverse Jiles-Atherton hysteresis model.

Application of Least-Squares Support-Vector Machine Based on Hysteresis Operators and Particle Swarm Optimization for Modeling and Control of Hysteresis in Piezoelectric Actuators

Nanopositioning systems driven by piezoelectric actuators are widely used in different fields. However, the hysteresis phenomenon is a major factor in reducing the positioning accuracy of piezoelectric actuators. This effect makes the task of accurate modeling and position control of piezoelectric actuators challenging. In this paper, the learning and generalization capabilities of the model are efficiently enhanced to describe and compensate for the rate-independent and rate-dependent hysteresis using a kernel-based learning method. The proposed model is inspired by the classical Preisach hysteresis model, in which a set of hysteresis operators is used to address the problem of mapping, and then least-squares support-vector machines (LSSVM) combined with a particle swarm optimization (PSO) algorithm are used for identification. Two control schemes are proposed for hysteresis compensation, and their performance is evaluated through real-time experiments on a nanopositioning platform. First, an inverse model-based feedforward controller is designed based on the LSSVM model, and then a combined feedback/feedforward control scheme is designed using a classical control strategy (PID) to further enhance the tracking performance. For performance evaluation, different datasets with a variety of hysteresis loops are used during the simulation and experimental procedures. The results show that the proposed method is successful in enhancing the generalization capabilities of LSSVM training and achieving the best tracking performance based on the combination of feedforward control and PID feedback control. The proposed control scheme outperformed the inverse Preisach model-based control scheme in terms of both positioning accuracy and execution time. The control scheme that uses the LSSVM based on nonlinear autoregressive exogenous (NARX) models has significantly less computational complexity compared to our control scheme but at the expense of accuracy.

Kalman filter and classical Preisach hysteresis model applied to the state of charge battery estimation

The goal of this work is first to include a hysteresis model in the classical equivalent circuit model (ECM) for a battery system and then to improve the estimation of the state of charge (SoC) by applying the Extended Kalman Filter (EKF). The hysteretic behavior of the open circuit voltage (OCV) is modelled with the classical Preisach model used for magnetic materials. The construction of the Preisach operator is made by means of the Everett function identified from experimental data which only involve the charging curves of the battery. Thus, a significant reduction in the time necessary to obtain the measurements is achieved. The model is assessed with some laboratory experiments performed on a lithium-ion battery and the results show that with this procedure hysteresis is very well reproduced, even when interior loops are present. In addition, the use of the EKF allows us to eliminate the measurements noise and ensure the accuracy of SoC estimation. The high computational efficiency and precision of the method, joined to the limited computational resources needed for the numerical implementation, make it particularly suitable for real-time embedded battery management system (BMS) applications. In addition, the proposed methodology is well-adapted to any battery type, independently of the SoC-OCV profile of the hysteresis cycle.

Improved estimation of iron losses for non-sinusoidal voltages

PurposeThe electrical machines connected to modern electric power grids are non-sinusoidal excited, and their augmented losses, including iron losses, limit their working characteristics. This paper aims to propose a prediction method for iron losses in non-oriented grains (NO) FeSi sheets under non-sinusoidal voltage, involving an inverse classical Preisach hysteresis model and the time-integration of each loss component.Design/methodology/approachThe magnetic history management in inverse Preisach model is optimized and a numerical Everett function is identified from measured symmetrical hysteresis cycles. The experimental data for sinusoidal waveforms obtained by a single sheet tester were also used to identify the parameters involved in Bertotti’ losses separation method. The non-sinusoidal magnetic induction waveform, corresponding to a measured voltage in an industrial electrical grid, was the input for Preisach model, the output magnetic field being accurately computed. The hysteresis, classical and excess losses are calculated by time-integration and the total losses are compared with those obtained for sinusoidal excitation.FindingsThe proposed method allows to estimate the iron losses for non-sinusoidal magnetic induction, using carefully identified parameters of FeSi NO sheets, using experimental data from sinusoidal regimes.Originality/valueThe method accuracy is assured by using a numerical Everett function, a variable Preisach grid step (adapted for the high non-linearity of FeSi sheets) and high-order fitting polynomials for the microscopic parameters involved in the excess loss estimation. The procedure allows a better design of magnetic cores and an improved estimation of the electric machine derating for non-sinusoidal voltages.

An Easy-to-Implement Hysteresis Model Identification Method Based on Support Vector Regression

The classical Preisach hysteresis model and its modifications are time consuming to implement due to the determination of the weight function. Another defect of the Preisach-based model is that it could only be an approximation in the absence of the congruency property. For such reasons, this paper proposes a hysteresis model identification method based on support vector regression which could be a promising alternative in practical applications. Support vector machine is attractive in regression analysis due to its strong generalization capability. A four-stage identification procedure is implemented and key techniques are introduced in detail. The penalty parameter and the kernel parameter are optimized using grid search and cross-validation method. The influences of data scaling and parameter optimization are analyzed. An identified hysteresis model of aluminum nickel cobalt alloy is evaluated and verified with the criteria of mean squared error and identified time.

Temperature characteristics modeling of Preisach theory

This paper proposes a modeling method of the temperature characteristics of Preisach theory. On the basis of the classical Preisach hysteresis model, the Curie temperature, the critical exponent and the ambient temperature are introduced after which the effect of temperature on the magnetic properties of ferromagnetic materials can be accurately reflected. A simulation analysis and a temperature characteristic experiment with silicon steel was carried out. The results are basically the same which proves the validity and the accuracy of the method.

Novel models for one-sided hysteresis of piezoelectric actuators

The hysteretic behavior of a plant with a non-negative input, referred to as one-sided hysteresis, is characterized by an initial ascending curve and hysteresis loops. It is observed that the widely-used classical Preisach hysteresis model and its modifications cannot represent such one-sided hysteresis due to the limitation of the Preisach hysteresis operator. To address this issue, a novel hysteresis operator modified from the Preisach hysteresis operator is proposed in this study and on this basis, a rate-independent hysteresis model and a rate-dependent hysteresis model are developed with methods to estimate their parameters. An algorithm to invert the rate-independent hysteresis model and its application to tracking control are also presented. The models and control schemes developed were verified experimentally on a commercially-available piezoelectric actuator. The results obtained show that the models developed are promising to represent the one-sided hysteresis of the piezoelectric actuator and that the inverting algorithm of the rate-independent hysteresis model is effective as applied to the tracking control of piezoelectric actuators.

Modeling of Piezoelectric Actuators Based on a New Rate-Independent Hysteresis Model

Accurate model representatives of piezoelectric actuators (PEAs) are important for both understanding the dynamic behaviors of PEAs and control scheme development. However, among the existing models, the most widely used classical Preisach hysteresis model are incapable of representing the commonly-encountered one-sided (non-negative voltage input range) hysteresis behaviors of PEAs. To solve this problem, a new rate-independent hysteresis model was developed for the one-sided hysteresis and then integrated with the models representative of creep and dynamics to form a single model for the PEAs. Experiments were carried out to validate the developed models.

Hysteresis in a Carbon Nanotube Based Electroactive Polymer Microfiber Actuator: Numerical Modeling

Hysteretic behavior is an important consideration for smart electroactive polymer actuators in a wide variety of nano/micro-scale applications. We prepared an electroactive polymer actuator in the form of a microfiber, based on single-wall carbon nanotubes and polyaniline, and investigated the hysteretic characteristics of the actuator under electrical potential switching in a basic electrolyte solution. For actuation experiments, we measured the variation of the length of the carbon-nanotube-based electroactive polymer actuator, using an Aurora Scientific Inc. 300B Series muscle lever arm system, while electrical potentials ranging from 0.2 V to 0.65 V were applied. Based on the classical Preisach hysteresis model, we presented and validated a numerical model that described the hysteretic behavior of the carbon-nanotube-based electroactive polymer actuator. Inverse hysteretic behavior was also simulated using the model to demonstrate its capability to predict an input from a desired output. This numerical model of hysteresis could be an effective approach to micro-scale control of carbon-nanotube-based electroactive polymer actuators in potential applications.

Modeling and Compensation of Hysteresis in Piezoceramic Transducers for Vibration Control

Hysteretic behavior in piezoceramic transducers is investigated theoretically and experimentally. The applicability of the rate-independent generalized Maxwell resistive capacitor (MRC) hysteresis model is established. Methods for MRC and inverse MRC online model identification are developed by first establishing that the MRC and its inverse are the same particular cases of the classical Preisach hysteresis model. This enables use of the extensive mathematical framework that has been developed for Preisach models. A method of incorporating the MRC model in a feed forward control scheme for hysteresis compensation is also presented. Experimental studies on a 1-3 piezoceramic composite support the theoretical developments and their applicability to piezoceramics.