Permanent Magnet Linear Synchronous Motor Research Articles

Hybrid Layer Modeling Method With Dual-Leakage Flux Paths for Heavily Saturated Iron-Cored Linear Permanent Magnet Synchronous Motors

This paper presents the dual-leakage hybrid layer modeling (DL-HLM) method for the linear permanent-magnet synchronous motors (LPMSMs) in a heavily saturated state. The proposed hybrid model consists of the nonlinear dual-leakage flux-tube model for the iron-cored armature where the geometric saliency exists, the Maxwell model for the PM track with uniform layers, and the hybrid input-output conversion method for the iteration between two models. As the minimum number of leakage flux paths, the dual-leakage flux-tube network is selected, considering the opposite-direction leakage fluxes generated by the flux-steering effect in heavily saturated iron-core teeth. The novel reluctance adaptation methods are also proposed, which allow the DL-HLM to accurately capture significant nonlinearities even with the minimum number of leakage flux paths, thereby correctly estimating motor forces in high-performance LPMSMs. The proposed DL-HLM is validated comparing to the equivalent finite element method (FEM) in terms of the magnetic fields in the working air-gap and motor force performances. The proposed modeling method estimates the magnetic fields and forces with an accuracy of higher than 95% even at significantly high saturation levels while simultaneously achieving multiple-orders-of-magnitude faster computation time as compared to the FEM.

A novel fixed‐time fractional order nonsingular terminal sliding mode control

AbstractIn order to reduce the convergence time of permanent magnet linear synchronous motor (PMLSM) and improve the robustness of system, a fixed‐time fractional order nonsingular terminal sliding mode control (FTFONTSMC) strategy is designed to realize the rapidity and accuracy of PMLSM position tracking response. Firstly, an improved fixed‐time terminal sliding mode (FTTSM) reaching law is proposed to reduce the time of convergence. Secondly, due to the uncertainty of the disturbance in PMLSM system, an exponential convergent disturbance observer (DO) is designed to observe the disturbance. Further, finite time stability of the control system is proved by Lyapunov stability theory. Finally, the above control algorithm is applied to PMLSM, and the proposed control method's effectiveness and superiority are validated by comparing with existing control methods.

Adaptive Jerk Control and Modified Parameter Estimation for PMLSM Servo System With Disturbance Attenuation Ability

The direct-drive industrial technology has put forward much higher requirements for the application of high-performance permanent magnet linear synchronous motor (PMLSM) servo system. To improve the control accuracy and transient performance, a novel disturbance attenuation approach is proposed based on adaptive jerk control (AJC) and modified parameter estimation for PMLSM servo system in this article. Within the control details, AJC is proposed to realize asymptotic stability without requiring <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a priori</i> knowledge of disturbances, which can release the strong restriction and eliminate the design conservation. Furthermore, a novel adaptive law is designed for feedback gain to further enhance the robustness when the system meets the challenge of high-gain feedback and measurement noise. Meanwhile, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ϵ</i> -modification parameter estimation is employed to approximate and compensate for the parameter variation, which can not only achieve fast convergence rate but also guarantee small overshoot. The asymptotic stability of the proposed control method is analyzed and proved by the Lyapunov theorem. Finally, the experimental results are presented to validate the efficiency with better disturbance attenuation ability.

Fractional-order feedforward control method for permanent magnet linear synchronous motor based on frequency-domain adjustment theory

For a permanent magnet linear synchronous motor motion system, following error is one of the key indexes used when the motion system is applied to high-performance manufacturing equipment. Owing to the uncomplete description of the motion system’s control frequency-domain characteristics, the integer-order feedforward control method adapted for a two-degree-of-freedom feedforward-feedback control system may result in large-trajectory following error. To address this problem, this paper proposes a fractional-order feedforward control method with the frequency-domain characteristics adjustment ability. For the proposed method, this paper constructs an equal-order fractional-order compensator to compensate the frequency-domain errors of the integer-order feedforward control method. According to the features of the equal-order fractional-order compensator, this paper decomposes the compensator into multiple independent units, clarifies the relationship between parameter selection and frequency-domain characteristics, and establishes an optimal solution formula for phase error minimization. Through compensator decomposition and optimal parameter determination, the proposed fractional-order feedforward control method can accurately describe the control frequency-domain characteristics of the motion system. The simulation experiment results show that the proposed method can effectively reduce the gain and phase errors. The physical experiments were conducted on a motion system constructed by permanent magnet linear synchronous motors. And the experiment results are presented herein to validate the effectiveness and advancements of the proposed method in high-precision motion control for the permanent magnet linear synchronous motor motion system.

Research on Air Gap Magnetic Field Characteristics of Trapezoidal Halbach Permanent Magnet Linear Synchronous Motor Based on Improved Equivalent Surface Current Method

Accurate analysis of the air gap magnetic field is the focus of research in the field of precision permanent magnet linear synchronous motors. In this paper, the two-dimensional air gap magnetic field of a secondary trapezoidal Halbach permanent magnet array coreless permanent magnet linear synchronous motor (PMLSM) was taken as our research object. On the basis of the equivalent surface current method, we proposed an improved equivalent analytical algorithm with a trapezoidal side length unit. The equivalent analytical model of the magnetic induction vector of the two-dimensional air gap was established, and the air gap magnetic field of the trapezoidal Halbach array coreless PMLSM was calculated. At the same time, we analyzed the influence of the bottom angle α of a trapezoidal permanent magnet equivalent width coefficient αw, pole height coefficient αh, and air gap height coefficient αg on the amplitude (Bpeak) and total harmonic distortion (THDB) of the central magnetic field in the air gap. The results show that α and αw have a significant influence on the Bpeak and THDB of the central magnetic field air gap. With the synergy of α and αw, we identified the “flux convergence” effect, which makes the maximum range of Bpeak α &gt; 90° and αw &lt; 0.5. We also found the “equilateral” effect, which causes the minimum region of THDB to change linearly. The calculation results of the improved equivalent surface current analytical model established in this paper agree with those verified by the finite element method. The calculation is convenient, and the accuracy of the result is high. This research provides a new method for analyzing the air gap magnetic field of a permanent magnet with a nonrectangular cross-section and lays a theoretical foundation for optimizing the PMLSM pole model.

Sliding-Mode Control for PMLSM Position Control—A Review

Owing to the competitive advantages of fast response speed, large pushing force, high reliability, and high precision, the permanent magnet linear synchronous motor (PMLSM) has played an increasingly vital role in various high-speed and high-precision control systems. However, PMLSM exhibits nonlinear behavior in actual operation, and position tracking precision is negatively affected by friction, load changes, and other external disturbances. To meet the growing demand and solve the position tracking control problem for the PMLSM, the control system is critical. Sliding-mode control (SMC) has been used extensively in nonlinear control systems due to its superior performance characterized by simplicity, good dynamic response and insensitivity to parameter perturbation and external disturbances, and has been implemented in PMLSMs to track practical position. The objective of this article is to classify, scrutinize and review the major sliding-mode control approaches for position control of PMLSM. The three different conventional SMC methods, namely the boundary layer approach, the reaching law approach and the disturbance observer-based SMC, are discussed in detail. The four advanced forms of SMC, namely terminal SMC, super-twisting SMC, adaptive SMC and intelligent SMC, are also presented. A comparison of these approaches is given, in which the advantages and disadvantages of each approach are presented; additionally, they are presented in table form in order to facilitate reading. It is anticipated that this work will serve as a reference and provide important insight into position control of PMLSM systems.

Optimal design of Udwadia–Kalaba theory-based adaptive robust control for permanent magnet linear synchronous motor

The control performance of permanent magnet linear synchronous motor (PMLSM) is limited by uncertainty. The uncertainty is bounded by an unknown bound and may be time-varying. The boundary information of uncertainty is unknown but can be described by fuzzy set theory. To mitigate the impact of uncertainty on control performance, this paper proposes a Udwadia–Kalaba theory-based adaptive robust control (UKBARC). The proposed controller contains a Udwadia–Kalaba theory-based controller and an adaptive robust controller. In the Udwadia–Kalaba theory-based controller, the expected trajectory is taken as the expected constraint, and then the control task is converted to make the expected constraint be followed. Additionally, the adaptive robust controller is introduced to handle the system uncertainty without requiring the boundary information of uncertainty. The Lyapunov method is used to show that the performance of uniform boundedness (UB) and uniform ultimate boundedness (UUB) for the PMLSM system is guaranteed. The objective function used to characterize the trade-off between performance and control cost can be derived based on the fuzzy description of uncertainty. Thus, the optimal design of UKBARC (OUKBARC) can be achieved by minimizing the objective function. Simulation and experiment results together verify that high precision motion control can be ensured by using the proposed approach.

Predictive Current Control of Sensorless Linear Permanent Magnet Synchronous Motor

In the vector control system of a tubular oscillating permanent magnet synchronous linear motor, it is difficult to obtain accurate feedback information from the conventional mechanical sensors under bad and complex working conditions. This paper presents a new predictive current control designed to estimate the speed of the tubular oscillation permanent magnet synchronous linear motor. It implements two control techniques: The first technique is using the sliding-mode observer’s speed observer for speed estimation. The second is to design a deadbeat predictive current control to replace the PI regulator in the conventional current loop; it solves the difficulties of global optimization and PI parameter setting. The simulation and experimental results show that this method gives a good dynamic performance.

Tangential and Normal Force Generation-Mechanism in Permanent Magnet Linear Synchronous Motors

Tangential and Normal Force Generation-Mechanism in Permanent Magnet Linear Synchronous Motors

Adaptive PID controller of permanent magnet linear synchronous motor based on particle swarm neural network

Adaptive PID controller of permanent magnet linear synchronous motor based on particle swarm neural network

DPMSLM Demagnetization Fault Detection Based on Texture Feature Analysis of Grayscale Fusion Image

This study investigates a novel image morphology texture feature extraction method to realize the demagnetization fault location and severity detection of double-sided permanent magnet synchronous linear motor (DPMSLM). Initially, according to the constraints of DPMSLMs topology structure, the three lines magnetic density signal in motor air gap is extracted by finite element analysis as effective fault signal. Then, the grayscale fusion image (GFI) method is introduced to transform 1D data signal to 2D fused grayscale image which can better describe the demagnetization fault information. The unique features are visualized using the image enhancement techniques, and the image morphology texture features such as the area, Euler number, perimeter operator, correlation of binary image and so on can be extracted to constitute the demagnetization fault indexes. In addition, fisher score (FS) is used for feature optimization which can reduce the feature dimension. Furthermore, the two-level multiverse optimization support vector machine (MVO-SVM) algorithm is established to conduct demagnetization fault classification. Comparison experiments with other classifiers show that the MVO-SVM has a high fault identification accuracy of more than 98.3% and low running time less than 2.57s. Finally, the motor prototype experiment results show that the proposed method can accurately identify the location and severity of DPMSLM demagnetization faults, and it is an effective and feasible method which can be applied in DPMLM batch demagnetization inspection before delivery.

Speed Control Strategy of Low-Cost Modular Permanent Magnet Synchronous Linear Motor Based on Sliding Mode Vector Tracking Observer

In order to achieve the low-cost position detection of modular permanent magnet synchronous linear motor (MPMSLM), three switching Hall sensors space 120° apart are designed. Two groups of Hall detection board are installed to ensure the position detection is effective throughout the process. The motor speed and electrical angle are extracted from Hall signals using Taylor expansion. In addition, a sliding mode observer (SMO) is designed to estimate the back EMF. Then, the information of SMO and Hall sensors is integrated by vector tracking observer. Eventually, a closed-loop speed control system based on sliding mode vector tracking observer is established. The experiments are carried out on the linear segment of MPMSLM. The results show that the proposed method can estimate motor speed and electrical angle accurately at the full-speed range.

Bond Graph Modeling, Simulation, and Control of Permanent Magnet Linear Synchronous Motor

The high-performance feature of the Permanent Magnet Linear Synchronous Motor (PMLSM) makes it a reliable and valuable motor for use in the automotive industry, especially for electric vehicle (EVs) applications. This research proposes a bond graph approach in modeling the PMLSM as a multi-domain dynamical system. However, A time-based simulation was performed using 20-sim software to simulate the dynamical behavior of the motor. An equivalent model of the motor was first obtained and then modeled and simulated using 20-sim software. The model of the PMLSM drive system was modeled separately and incorporated with PMLSM Motor equivalent model to form a global model. Moreover, the motor drive system response was studied based on the sensor resolutions and the inverter switching frequency. The block diagram and the transfer function methods validated the bond graph model obtained. Two classical PIs such as continuous and discrete were implemented on the motor response to control the velocity of the motor.

Detent force suppression of permanent magnet linear synchronous motor based on a V‐shaped tooth‐slot structure

AbstractGiven the existence of detent force, the positioning accuracy of permanent magnet linear synchronous motor (PMLSM) with an iron core worsens in its application in the field of the precision drive. To address this problem, a method is proposed to weaken the detent force of PMLSM with a V‐shaped tooth‐slot structure. The models of the detent force, including the cogging force and end force, are established theoretically. The analytical expressions of cogging force and end force are obtained by analysing the ripple rule of the motor. Then, the tooth‐slot surface of the motor with the V‐shaped tooth‐slot structure conducts infinitesimal processing. The relationship between cogging force, end force, and the V‐shaped depth of the V‐shaped tooth‐slot PMLSM is deduced, respectively, using the integration method. Furthermore, Ansoft finite element simulation software Maxwell module is used to compare the conventional PMLSM, V‐shaped magnetic pole PMLSM, and V‐shaped tooth‐slot PMLSM. The comparison reveals that the V‐shaped tooth‐slot structure has the excellent characteristic of increasing the average value of thrust while reducing the ripple of thrust caused by detent force. Finally, prototype fabrication and experiments are conducted to verify the correctness and feasibility of the proposed method.

Influence of the Machining Process on the Thrust Force and Mechanical Characteristics for the Direct Drive System

This paper investigates the effects of the machining process on the thrust force and mechanical characteristics for the direct drive feed system driven by the flat permanent magnet synchronous linear motor (PMSLM) in machine tools considering the electromechanical couplings. Firstly, the cutting force in the machining process is researched. Then, the analytical model of the direct drive feed system is established and analyzed. The electromechanical couplings between the mechanical system and servo system in the direct drive feed system are studied. Furthermore, the influences of the cutting force on different couplings are analyzed, and the thrust force characteristic is analytically represented. Finally, the validity of the theoretical analysis is verified by the experiments, and the effects of the machining process on the dynamic precision of the feed system are discussed. The results show that the electromechanical couplings in the direct drive system will aggravate the effects of the machining process on the thrust force and mechanical characteristics of the feed system. A large number of new paired thrust harmonics will be produced. The influence of the machining process on the mechanical system will be extended from the discrete frequency point caused by the cutting force to the approximate frequency band caused by the thrust force, affecting the dynamic precision of the feed system and the cutting stability of the machine tool.

Model predictive and compensated ADRC for permanent magnet synchronous linear motors

Traditional linear active disturbance rejection control (LADRC) may have difficulty to achieve a rapid precise disturbance rejection for a permanent magnet synchronous linear motor (PMSLM). By making use of model information, a model predictive and compensated LADRC (MPLADRC) method is proposed in this paper. In this method, a model compensated extended state observer (MESO) is designed to transform the controlled object into an established mathematical model through total disturbance compensation. Meanwhile, considering the delay problem of MESO, a phase advance module is designed to improve the estimation speed of MESO for system disturbance and state, thus the MESO can rapidly compensate various uncertainty disturbances to the controlled object in real time. The model predictive controller (MPC) is then designed based on the mathematical model, and its optimal control law is then obtained through a quadratic objective function to further suppress the disturbance unobserved by the designed MESO. The proposed method can thus realize a dual-degree-of-freedom disturbance rejection through the MESO and MPC. The simulation and experimental results validate the effectiveness of the proposed MPLADRC in rapid anti-disturbance and fast positioning for the motion control of the PMSLM.

A novel electromagnetic recuperator used in the artillery: Structural and control algorithm design

Aiming at the problem that the traditional artillery recuperator is difficult to maintain and control, a novel electromagnetic recuperator based on the principle of tubular permanent magnet synchronous linear motor is proposed. First, the structural scheme of the electromagnetic recuperator is designed, and the maximum thrust required for the artillery counter-recoil motion process is determined by force analysis. Secondly, according to the requirements of the artillery type and design, the analytical model of the electromagnetic recuperator is established by the subdomain method, and the main structural parameters can be obtained quickly. Then, the correctness of the analytical model is verified by the finite element method. Considering the complex uncertainties in the artillery counter-recoil control process, an adaptive robust control is proposed. The uncertainty of the system is estimated online using a leaky adaptive rate α, and the controller is compensated. Finally, the simulation results show that the designed electromagnetic recuperator meets the thrust requirements of the artillery counter-recoil process; adaptive robust control can effectively solve the uncertainty problem in the system and provides smaller stabilization time and steady-state tracking error compared to PID control.

Structural design and performance prediction of novel modular tubular permanent magnet linear synchronous motor

The limitation of the primary core length of the tubular permanent magnet synchronous linear motor (TPMSLM) causes large thrust ripples during operation. To end this, a modular TPMSLM with two units is proposed. The principle of its suppression of end effects is derived, and utilization of the three-phase winding is improved using the star vectograms of the back electromotive force (EMF). Afterward, an equivalent subdomain method is adopted to analyze the above structure. This method combines the subdomain and the equivalent magnetic circuit (EMC) model, and the comparison with nonlinear FEM verifies its effectiveness. Using this integrated approach, reasonable structure parameters are selected. Finally, the experimental platform of the two-unit modular TPMSLM prototype is built with the selected structural parameters. Good agreement between the simulation and the experiment on the back EMF, detent force, and the prototype's static thrust verifies the new structure's feasibility.

Physics-Informed Generative Adversarial Network-Based Modeling and Simulation of Linear Electric Machines

The demand for fast magnetic field approximation for the optimal design of electromagnetic devices is urgent nowadays. However, due to the lack of a publicly available dataset and the unclear definition of each parameter in the magnetic field dataset, the expansion of data-driven magnetic field approximation is severely limited. This study presents a physics-informed generative adversarial network (PIGAN), as well as a permanent magnet linear synchronous motor (PMLSM)-based magnetic field dataset, for fast magnetic field approximation. It includes the current density, material distribution, electromagnetic material properties, and other parameters of the electric machine. Physics-informed loss functions are utilized in the training process, making the output governed by Maxwell’s equation. Different slot-pole combinations of the PMLSM are involved in the dataset to extend the generalization of PIGAN. Some indicators for the further evaluation of magnetic approximation performance, including image-based metrics and calculation methods for the performance of electric motors, are presented in this study. Some challenges of magnetic field approximation using PIGAN are also discussed. The effectiveness of the physics-informed method is verified by comparing the magnetic field approximation results and the performance analysis results of the PMLSM with FEM, and the speed of PIGAN is approximately 40 times faster than that of FEM, while the accuracy is similar.

Full-coefficient Intelligent Adaptive Position Control of Permanent Magnet Synchronous Linear Motor

Full-coefficient Intelligent Adaptive Position Control of Permanent Magnet Synchronous Linear Motor