Giant Magnetostrictive Actuator Research Articles

Nonlinear Dynamic Analysis of Riemann–Liouville Fractional-Order Damping Giant Magnetostrictive Actuator

Abstract In view of the large errors in the integer-order prediction model of the current giant magnetostrictive actuator (GMA), existing studies have shown that the fractional-order theory can improve the classical integer-order error situation. To this end, the Riemann–Liouville (R–L) fractional-order calculus theory is applied to the damping part of the GMA system; based on the averaging method and the power series method, the analytical and numerical solutions of the system are obtained, respectively, the motion of the GMA system is obtained through simulation, the parameters affecting the main resonance response of the system are analyzed as well as the motion characteristics of the system under the parameters, and the bifurcation and chaotic characteristics of the system are analyzed qualitatively and quantitatively. It is shown that the fractional-order model can improve the prediction accuracy of the system, the fractional order has a significant effect on the motion of the system, and the interval of the periodical motion parameter is less than an integer when the order of the damping term is (0,1), and the system can be induced to shift to periodic motion by changing the parameters.

Structural Optimization of a Giant Magnetostrictive Actuator Based on BP-NSGA-II Algorithm

This study introduces an integrated structural optimization design method based on a BP neural network and NSGA-II multi-objective genetic algorithm. Initially, a two-dimensional axisymmetric finite element model of the Giant Magnetostrictive Actuator (GMA) was established, and the coupling simulation of the electromagnetic field, structural field, and temperature field was conducted to obtain the GMA’s performance parameters. Subsequently, the structural parameters of the GMA magnetic circuit, including the magnetic conducting ring, magnetic conducting sidewall, magnetic conducting body, and coil, were used as inputs, and the axial magnetic induction intensity, uniformity of axial magnetic induction intensity, and coil loss on the Giant Magnetostrictive Material (GMM) rod were used as outputs to establish a back propagation (BP) neural network model. This model delineated the nonlinear relationship between structural parameters and performance parameters. Then, the BP-NSGA-II algorithm was applied to perform multi-objective optimization on the actuator’s structural parameters, resulting in a set of Pareto optimal non-dominated solutions, from which a set of optimal solutions was obtained using the entropy weight method. Finally, simulation analysis of this optimal solution was conducted, indicating that under a 5 A power supply excitation, the maximum axial magnetic induction intensity on the optimized GMM rod increased from 0.87 T to 1.12 T; the uniformity of axial magnetic induction intensity improved from 93.1% to 96.5%; and the coil loss decreased from 7.79 × 104 W/m3 to 4.97 × 104 W/m3. Based on the optimization results, a prototype actuator was produced, and the test results of the prototype’s output characteristics proved the feasibility of this optimization design method.

Experimental study on synchronous detection of output force in a self-sensing giant magnetostrictive actuator

This paper systematically investigates the real-time detection of static and dynamic output forces by a self-sensing giant magnetostrictive actuator (SSGMA). The online stiffness of the actuator is perceived as the sensing signal according to the ΔE effect of Terfenol-D. Numerical simulations are carried out to analyze the effects of the driving magnetic field and the hysteresis caused by magneto-mechanical coupling on the performance of self-sensing output force. Then the prototype is fabricated and tested to verify the self-sensing characteristics of SSGMA for the output force. The noise density of prototype is tested to be below 56.92 nV √Hz−1. The experimental results illustrate that SSGMA has a self-detection sensitivity of 0.47 mV N−1 for a static force with an amplitude of nearly 120 N. The SSGMA is able to synchronize the tracking of quasi-static and low-frequency dynamic output forces, respectively. The hereby proposed SSGMA further broadens the application scenario of precision actuation systems by synchronizing the detection and control of the output force without requiring external sensors.

A nonlinear dynamic hysteresis model with magnetic–prestress–thermal coupling effect and dynamic electromagnetic losses of a giant magnetostrictive actuator

Compared with traditional actuators, the giant magnetostrictive actuator has the merits of fast response, high accuracy, and high reliability and has been widely applied. However, its performance is affected by the electromagnetic loss and the temperature, prestress, and magnetic coupling effect. In order to accurately analyze its performance, it is necessary to establish a nonlinear dynamic model including the electromagnetic loss and the magnetic–prestress–thermal coupling effect. First, based on the field separation approach, the magnetic fields generated by the eddy current loss and the anomalous loss are obtained and added to the Jiles–Atherton model. Second, the magnetostrictive model is given with the magnetic–prestress–thermal coupling effect. Finally, assuming the transmission of the giant magnetostrictive actuator as a mass–spring–damper system, a nonlinear dynamic hysteresis model with magnetic–prestress–thermal coupling effect and dynamic electromagnetic losses of a giant magnetostrictive actuator is developed. Based on this model, the output displacement curves of the giant magnetostrictive actuators under different driving currents and frequencies are given. The comparison with the experimental results shows that this model agrees well with the experiment.

Decentralized Implicit Inverse Control for Large-Scale Hysteretic Nonlinear Time-Delay Systems and Its Application on Triple-Axis Giant Magnetostrictive Actuators.

This article proposes fuzzy-logic systems (FLSs)-based decentralized adaptive implicit inverse control scheme for a class of large-scale nonlinear systems with time delays and multihysteretic loops. Our novel algorithms feature hysteretic implicit inverse compensators designed to effectively mitigate multihysteretic loops in large-scale systems. In this article, hysteretic implicit inverse compensators can replace the traditional hysteretic inverse models, which are exceedingly difficult to construct, and no longer necessary. The authors provide three contributions: 1) a searching mechanism to obtain the approximate value of the practical input signal from the so-called hysteretic temporary control law; 2) the arbitrarily small L∞ norm of the tracking error attained by utilizing the proposed initializing technique, which applies the combination of FLSs and a finite covering lemma to deal with time delays; and 3) the construction of a triple-axis giant magnetostrictive motion control platform, which validates the effectiveness of the proposed control scheme and algorithms.

Magneto-Mechanical Coupling Analysis of Automobile Brake by Wire System Based on Giant-Magnetostrictive Actuator

Addressing the drawbacks of traditional automotive braking systems, including long hydraulic lines, heavy weight, and slow response speed, a new type brake by wire system based on giant-magnetostrictive material is proposed, which consists of giant-magnetostrictive actuator module and mechanical drive module. In this paper, CATIA software is used to establish a three-dimensional model of the brake. In order to verify the reliability of the model, giant-magnetostrictive actuator is taken as the research object, and COMSOL software is used to simulate different working conditions of automobile braking. A Magneto-mechanical coupling model was established and Magneto-mechanical coupling analysis of the actuator was carried out. The simulation results show that the aluminum shell material is superior to the 45 steel shell material. The inductance direction of the actuator is approximately elliptical from top to bottom, with uniform distribution of magnetic flux density and stress. The output stress is 5e4N/m2, and the maximum elongation is 0.1071mm. Finally, the driving efficiency of GMA was verified on an optical isolation platform, and comparative experiments were conducted before and after optimization using instruments such as laser displacement samplers, Tesla meters, and force sensors. The experimental results indicate that by optimizing the housing material and structure of the actuator, the displacement increased from 0.05188mm to 0.1003mm, magnetic induction increased from 42.9mT to 79.9mT, resulting in an increase of 41.6% and 42.7% respectively, and the maximum output force was 4752.3N. It makes a certain contribution to the application of GMA to automotive braking field and further proves the effectiveness of GMA in the application of automobile brake by wire system.

Co-simulation of giant magnetostrictive autonomous emergen-cy braking system for intelligent vehicles based on Prescan/Simulink /CarSim

The combination of giant magnetostrictive actuator (GMA) and autonomous Emergency brak-ing system (AEB) can achieve the lightweight body and fast braking of intelligent vehicle. In this essay, simulation scenarios are established in PreScan, AEB algorithm and GMA actuator are combined in simulink, vehicle dynamics model is provided by CarSim, and co-simulation analysis of CCRm, CCRs and CCRb working conditions is carried out. When AEB adopts TTC algorithm only, in the stationary vehicle scenario (CCRs) where the vehicle approaches the front at a certain speed, the relative distance between the two vehicles is between 1.86 and 2.85m until stopping. When the front vehicle is driving slowly and the ego vehicle is faster than the front (CCRm), the relative distance between the two vehicles until stopping is between 2.28 and 2.83m; When the ego vehicle is driving at the same speed as the front, the front vehicle suddenly braking (CCRb), and the relative distance between the two vehicles until stopping is 1.98~2.54m; The above scenarios can achieve effective collision avoidance, and the safety distance is within an effective and reasonable range. In the scenario of two vehicles following at the same speed and close distance, TTC algorithm fails. AEB adopts TTC algorithm and Seungwukmoonalgo-rithm for collaborative control to achieve effective collision avoidance. The co-simulation re-sults show that the AEB system can intervene in time and avoid collisions effectively under the above three working conditions, and the relative distance between the two vehicles until stop-ping is between 1.86 and 2.85m, which verifies the timeness and effectiveness of the braking of the giant magnetostrictive actuator when AEB algorithm intervenes, and significantly improves the active safety performance of the vehicle.

Precision positioning based on temperature dependence self-sensing magnetostrictive actuation mechanism

The self-sensing actuator that integrates both actuation and sensing functions is an effective way to simplify the structure of electromechanical systems. This paper proposes a temperature-dependent self-sensing actuation strategy based on a self-sensing giant magnetostrictive actuator (SSGMA) by sensing online stiffness. Utilizing the developed model considering temperature-dependent hysteresis nonlinearity, the self-sensing output characteristics of SSGMA are first evaluated. The self-sensing based control system is then designed in detail. The relationship between the self-sensing signal and the output displacement of SSGMA at different temperatures is constructed by General Regression Neural Network (GRNN) model for fast recognition by the controller. On this basis, a composite control scheme that takes into account rate-dependent asymmetric hysteresis nonlinearities and combines an adaptive feedforward controller with PID feedback controller is proposed for precision actuation of SSGMA. Finally, a temperature-controlled experimental platform is assembled for verification. Experimental results demonstrate that, based on the developed model, the SSGMA is capable of accurate self-sensing output at temperatures of 22 °C, 40 °C, and 70 °C, respectively. The SSGMA with the proposed control method enables the synchronous and precise self-sensing positioning of step and multiple-frequency sinusoidal expectations at different temperatures.

Fractional order time-delayed feedback control of hysteresis dynamics in giant magnetostrictive actuators

Fractional order time-delayed feedback control of hysteresis dynamics in giant magnetostrictive actuators

Study of the effects of fractional order and damping coefficient on the dynamics of giant magnetostrictive actuators

Study of the effects of fractional order and damping coefficient on the dynamics of giant magnetostrictive actuators

Development of Giant Magnetostrictive Materials for an Active Noise Control System in an Ultracompact Electric Vehicle

Recently, ultracompact electric vehicles (EVs) have begun to be sold, instead of general vehicles equipped with gasoline engines, for transportation. However, because the outer plate of an ultracompact EV has low rigidity, the road noise generated by rotation and the wind noise generated from the vehicle's projection shape are transmitted to the inside of the EV. This interior noise reduces the ride comfort for passengers. Therefore, an active noise control (ANC) system was proposed for controlling noise transmitted from the outside of the EV. The proposed ANC system was configured to control the sound generated using a giant magnetostrictive actuator on the wall surface in the cabin of the EV, instead of a vehicle installation speaker.In this study, Tb, Dy, and Fe powders, which are giant magnetostrictive materials, were mixed and mechanically alloyed to produce multiple giant magnetostrictive materials to be used in the proposed ANC system. The displacement of each alloyed giant magnetostrictive material was measured. In addition, each alloyed material was analyzed using X-ray diffraction and their crystal orientation was confirmed.

Rate-Dependent Hysteresis Model of a Giant Magnetostrictive Actuator Based on an Improved Cuckoo Algorithm

A rate-dependent asymmetric Prandtl–Ishilinskii (RAPI) model was proposed to tackle the serious rate-dependent hysteresis nonlinearity of the giant magnetostrictive actuator(GMA) output. First, a polynomial function was introduced based on the PI model, and hysteresis factors were introduced to the Play operator, which accurately described the asymmetrical characteristic of the actuator output. On this basis, rate-dependent parameters were added to establish a rate-dependent RAPI model. Second, an improved cuckoo search (ICS) algorithm was proposed to solve the difficulty in the parameter identification of the RAPI model. For the ICS algorithm, the algorithm stability and optimization accuracy were improved using the adaptive step (AS) strategy and bird’s nest disturbance strategy. Then, the effectiveness of the ICS algorithm was tested by comparing it with other parameter identification algorithms. Finally, the rate-dependent RAPI model was verified by combining the output data of the giant magnetostrictive actuator under different frequencies. The results show that the rate-dependent RAPI model exhibits a higher accuracy than the PI model, thus verifying the effectiveness of the rate-dependent RAPI model.

Nonlinear dynamic characteristics of two-dimensional micro-positioning workbench based on giant magnetostrictive actuators

Studying the nonlinear dynamic characteristics of multi-field coupling of the giant magnetostrictive actuator (GMA) is one of the main ways to improve its output performance. Because of the problem that its multi-field coupling nonlinear dynamic characteristics are difficult to accurately describe, the multi-field coupled nonlinear dynamic model of GMA and two-dimensional micro-positioning workbench is established according to the Jiles–Atherton hysteresis model, magnetostrictive model, hysteresis nonlinear magnetic equation and the structural dynamics principle of GMA, respectively. The influence of equivalent damping coefficient, equivalent stiffness, and equivalent mass on the dynamic characteristics of each model is analyzed, and finally, the constructed model and the obtained law are experimentally verified. The results show that the displacement curve calculated by the model is consistent with the experimentally measured displacement curve, the influence of the equivalent damping coefficient, equivalent stiffness, and equivalent mass on the dynamic characteristics of the model measured by the experiment is consistent with the simulation analysis results, and the maximum error of the output displacement is 1.779 um, which verifies the correctness of the model. The research results provide a theoretical basis for improving the dynamic characteristics of GMA and improving the output performance of two-dimensional micro-positioning workbenches.

Magnetic Circuit Optimization and Physical Modeling of Giant Magnetostrictive Actuator

Due to the excellent performance, giant magnetostrictive actuator is used in the active vibration isolation control system. However, its hysteresis nonlinear dynamic model is too complex for engineering practical applications, so it is necessary to establish an accurate and easy-to-use model. Based on Simulink/Simcape, a magnetic circuit model and a nonlinear dynamic physical model of the giant magnetostrictive actuator are developed. In the optimization of the magnetic circuit, the uniform distribution and the magnetic energy utilization of the giant magnetostrictive actuator are taken as the optimization objective, and the design criteria of the magnetic circuit are given. The hysteresis performance between the current and the magnetization is analyzed by simulating the magnetic circuit model. From the perspective of energy conservation, a linear magnetostrictive model which can reflect the effects of the frequency doubling and preload is established. Finally, the accuracy of the nonlinear dynamic physical model for the giant magnetostrictive actuator is verified by an experiment. The results show that the physical model agrees well with the experiment results not only under the quasistatic operating conditions but also under dynamic operating conditions. The error of the output displacement of the GMA under step response is less than 0.6 μm.

A precision-drive hysteresis model with an equal-density weight function for GMA feedforward compensation

Giant magnetostrictive actuators (GMAs) are a widely used type of micro-nano actuator, and they are greatly significant in the field of precision engineering. The accuracy of a GMA often depends on its hysteresis model. However, existing models have some limitations, including the difficulty of identifying their parameters and the tradeoff between the quantity of modeling data required and the level of precision achieved. To solve these problems, in this paper, we propose a Preisach inverse model based on equal-density segmentation of the weight function (E-Preisach). The weight function used to calculate the displacement is first discretized. Then, to obtain a finer weight distribution, the discretized geometric units are uniformly divided by area. This can further minimize the output displacement span, and it produces a higher-precision hysteresis model. The process of parameter identification is made easier by this approach, which also resolves the difficulty of obtaining high precision using a small amount of modeling data. The Preisach and the E-Preisach inverse models were investigated and compared using experiments. At frequencies of 1 and 5 Hz, it was found that the E-Preisach inverse model decreases the maximum error of the feedforward compensation open-loop control to within 1 µm and decreases the root-mean-square error in displacement to within 0.5 µm without the need to increase the number of measured hysteresis loops. As a result, the E-Preisach inverse model streamlines the structure of the model and requires fewer parameters for modeling. This provides a high-precision modeling method using a small amount of modeling data; it will have applications in precision engineering fields such as active vibration damping and ultra-precision machining.

Development of an ANC System with a Giant Magnetostrictive Actuator for Ultra-Compact Electric Vehicles: Thrust Force Characteristics Including Road Noise Range

Ultra-compact electric vehicles (EVs) have been recently sold as next-generation vehicles. However, they are yet to reach a notable phase of expansion and use. Ultra-compact EVs have compact and lightweight bodies. As the outer plate of an ultra-compact EV has low rigidity, the road noise generated by the tires and the wind noise generated from the vehicle’s projection shape are transmitted to the interior of the vehicle. Therefore, a new active noise control (ANC) system with a giant magnetostrictive actuator for ultra-compact EVs has been recently proposed. The giant magnetostrictive actuator is required to produce sufficient thrust, with less distortion, and delayed sound waves. In this work, we studied the thrust force characteristics of the giant magnetostrictive material, including in the road noise range. We considered the giant magnetostrictive thrust for output, including in the road noise range, using a finite element model of the giant magnetostrictive actuator by conducting an electromagnetic field analysis. The results showed that the effect of the thrust on the frequency changes depending on the length of the giant magnetostrictive material.

Parameter Identification of Displacement Model for Giant Magnetostrictive Actuator Using Differential Evolution Algorithm

Based on Jiles–Atherton theory and the quadratic law, a displacement model for giant magnetostrictive actuators (GMA) has been developed. The Runge–Kutta method is used to solve the nonlinear differential equation of the hysteresis model in a segmented magnetic field. Aiming at the problem that the model parameters are coupled with each other and difficult to estimate, a heuristic intelligent search algorithm-differential evolution algorithm (DE) is employed to implement parameter identification. In order to verify the effectiveness of the algorithm, comparative studies with the genetic algorithm (GA) and the particle swarm optimization (PSO) applied in parameter identification are performed. The simulation results demonstrate that the algorithm has the advantages of requiring few control variables, fast convergence speed, stable identified results, and excellent repeatability. Furthermore, the experimental results demonstrate that the output displacements calculated from the identified model are in great agreement with the measured values. Accordingly, the DE can identify the parameters of a displacement model for giant magnetostrictive actuators with satisfactory accuracy and reliability.

The improved giant magnetostrictive actuator oscillations via positive position feedback damper

<abstract><p>This article contemplates the demeanor of the giant magnetostrictive actuator (GMA) when a positive position feedback (PPF) damper is used to enable tight control over its vibration. The methodology followed here mathematically searches for the approximate solution for the motion equations of the GMA with the PPF damper, which has been accomplished by using one of the most famous perturbation methods. The multiple scale perturbation technique (MSPT) of the second-order approximation is our strategy to obtain the analytical results. The stability of the system has also been investigated and observed by implementing frequency response equations to close the concurrent primary and internal resonance cases. By utilizing Matlab and Maple programs, all numerical discussions have been accomplished and explained. The resulting influence on the amplitude due to changes in the parameters' values has been studied by the frequency response curves. Finally, a comparison between both the analytical and numerical solutions using time history and response curves is made. In addition to the comparison between our PPF damper's effect on the GMA, previous works are presented. To get our target in this article, we have mentioned some important applications utilized in the GMA system just to imagine the importance of controlling the GMA vibration.</p></abstract>

Displacement Model of Giant Magnetostrictive Actuator for Direct-Drive Injector

Aiming at the inherent problems of non-direct-drive injectors, such as long oil circuits and a difficult precise control of the needle stroke, based on the structure of a direct-drive injector and combined with the demand for the needle drive of a truck diesel injector, this study designs and fabricates a giant magnetostrictive actuator for direct-drive injectors. A simplified model of a giant magnetostrictive actuator is established, which mainly simplifies the magnetization model to facilitate the subsequent integrated modeling of the fuel injector. An actuator output displacement test system was built, and the output waveform and frequency characteristics of the actuator were analyzed. It was found that the experimental results were in good agreement with the calculated results of the model, and the average relative error of the amplitude was 3.26%, while the average relative error of the phase difference was 3.83%, which verifies the correctness of the model. This research enriches the modeling method of giant magnetostrictive actuators and has an important reference value for the research and design of fuel injectors.

Controller Design of a Brake-By-Wire System Based on Giant-Magnetostrictive Material for an Intelligent Vehicle

Mechatronics control technology can not only improve the performance of vehicles but also solve traditional automotive braking system problems such as long brake pipeline, lots of valve components, slow response and so on. In this paper, a giant-magnetostrictive actuator and a disc brake structure were used to build a drive control system, and the control system module was designed with a single-chip microcomputer as the core. Combined with sensor selection, software programming control was used to build the experimental test platform, and the maximum output displacement of the control system was 0.112156 mm, which was basically consistent with the theoretical calculation. The maximum output force was 3883 N, which exceeded the minimum output force of 3631 N calculated theoretically. According to the results of the test platform, the relevant test parameters were highly consistent with the theoretical calculation, which verified the correctness and effectiveness of the theoretical calculation and bench testbed design. It contributes to the improvement of vehicle active safety performance and can provide a new way for the development of an intelligent vehicle brake-by-wire system.