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Possible options for the design of a linear motor with a flexible secondary element have been considered. Analysis of the designs was carried out through simulation in Ansys Maxwell. A comparison of the simulation results was conducted, and the most promising design option was identified.

The paper provides an analysis of a transportation system with a long stator linear drive. The presented analysis for an in-house transportation system may be easily scaled into large transportation systems like maglev and hyperloop. It investigates the impact of the division of the stator into shorter parts which are sequentially supplied. Then it compares the concept of single-inverter and multi-inverter drive systems. The presented research includes the analysis of drive system power parameters. The drive system characteristics depending on the length of the active part of the linear motor are presented for each configuration, followed by a description of differences in the required inverter power and the obtained average thrust force. The paper proposes a new arrangement of the multi-inverter drive system incorporating multi-level inverters, which allows decreasing voltage oscillations in the DC circuit of drive inverters. The operation of the transportation system is presented in a simulation study. The paper is concluded with the verification of the concept in an experimental study in a 50 m test track.

Linear sliders are linear actuators using linear motors. It is used in many applications, such as factory lines and linear motor cars. In recent years, the demand for smaller semiconductor devices has been increasing due to the proliferation of smartphones. High-precision positioning of linear motors is needed because manufacturing semiconductor devices uses the stage with linear motors. However, linear motors have nonlinearity due to the position dependence of interlinkage flux. It affects precise positioning. In this study, the nonlinear characteristics due to the position dependence of the flux are expressed as a mathematical model by using a distributed constant magnetic circuit. A method compensating it using an operator-based feedback controller with the obtained mathematical model is proposed. The effectiveness of the proposed method is confirmed by simulating and experimenting with the reference following disturbance elimination.

The moving-magnet linear motor has received considerable attention in the development of logistic and factory automation in recent years. A reliable position detection system is the key to achieving the precise position and control of the motor. At present, the magnetic grid-scale and grating-scale are the most widely used traditional detection methods. However, these are not suitable for position detection with moving-magnet linear motors. They have the disadvantages of being easy to disturb, having a high cost, and exhibiting a limited measurement range. In this work, a moving-magnet linear motor position detection system based on an array of magnetoresistive sensors is used. The array is configured by arranging the magnetoresistive sensors at equal intervals along a line parallel to the trajectory of the armature. Then, the permanent magnet is fixed on the rotor and detected by sensors. When the rotor crosses the sensors in a parallel line, the changes in the magnetic field cause the magnetoresistive sensors to output two voltage signals directly proportional to the corresponding position changes. The signals are collected by the AD7606 and transmitted to the FPGA and STM32 controller for data processing, and the actual position of the rotor is calculated. This method has no length limitation and can be used for long-distance position detection. The experimental results show that the position detection system has a higher linear correlation coefficient compared with the magnetic grid ruler, in addition to a capability of ±9 μm accuracy, which verifies the validity of the position detection method for the moving-magnet linear motor.

The cylinder linear induction motor (CLIM) is a variation of the rotary induction motor. Its structure is simple, it has a low manufacturing cost, and it can generate linear thrust without the need for a conversion mechanism. It is particularly suitable for electromagnetic catapults, magnetic levitation transport, and industrial production fields, due to its strong environmental adaptability. Designing a high-thrust and high-efficiency CLIM is a great challenge due to its inherent drawbacks, such as the low thrust density and power density of induction motors. In this article, two CLIMs with different topologies are proposed to meet the demand for control-rod drives in high-temperature and high-pressure environments. The article elucidates the topologies of the two CLIMs and proposes an analytical computational approach for the CLIM. Modern optimization algorithms were utilized to optimize the design of the structural parameters of both CLIMs. A 3D-FEA simulation was used to compare and analyze the air-gap magnetism and thrust characteristics of two CLIMs. The results indicate that the copper-ring secondary CLIM has a higher thrust density and is more suitable for use in control-rod drive mechanism (CRDM) systems.

Free-piston engine generators without a crank mechanism are expected to be used in series hybrid vehicles because of their lower losses. The series hybrid system requires a low starting thrust because the engine frequently starts depending on the battery state. This study clarifies the effectiveness of the constant thrust resonance starting method that utilizes the compression pressure of the engine and the spring thrust. The piston must pass the combustion starting point with a predetermined speed to start combustion. Herein, we present a thrust setting method that uses the energy state diagram to optimize the velocity at the combustion start point. A simulation is performed assuming output when mounted on a vehicle. Consequently, the simulation results show that the maximum thrust can be reduced by more than 90% compared to that without resonance. Moreover, the speed at the combustion start point is in agreement with the value obtained using an energy state diagram. An impulse-like combustion pressure is generated in 180 ms, and combustion can be started using resonance, as shown in an experiment using a small-output engine and linear motor. The effectiveness of the constant thrust resonance starting method was confirmed.

This paper presents a novel means of sensorless drive of the winding segmented permanent magnet linear motor (WS-PMLM). In order to solve the problem of the deviation of the position and speed estimation of the mover caused by the sharp changes of the inductance, flux linkage, and back electromotive force (EMF) between the segments of the WS-PMLM, a method for position estimation by the compound back-EMF is proposed to eliminate the blind spot of intersegment position estimation. In terms of speed estimation, a full-order speed observer method based on the dynamics equation is proposed, the configuration of the feedback gain of the observer is analyzed, and a simulation is used to verify that the full-order state observer (FSO) method can effectively reduce the estimated speed fluctuation in the intersegment region and that the speed estimation accuracy is ultimately improved.

This state-of-the-art handbook covers most progressive and oscillatory linear electric machines (LEMs), drives, and MAGLEVS. It discusses basic and advanced modeling, steady state, transients, control, design, and testing of linear machines and drives with numerous case studies related to representative applications. Readers get ready-to-use knowledge of the analysis, design, control, testing, and ordering of linear electric machines, drives, and Maglevs to suit best various applications from people movers to industrial transport and linear oscillatory machines (loudspeakers, plunger solenoids, compressor drive, linear generators, or automotive active dampers and electromagnetic valve actuators for ICEs).

In this research, we propose a fixed-time sliding mode controller using a prescribed performance control approach to address the speed tracking problem in linear motor traction systems, which are powered by high-power permanent magnet linear synchronous motors (PMLSMs). Initially, to tackle the issue of the convergence time and dynamic response associated with traditional finite-time sliding mode controllers, we introduce a fixed-time sliding mode controller. This controller guarantees that the system state converges to the origin within a specified upper time limit. Subsequently, to enhance the dynamic response of the PMLSM and minimize speed errors, we integrate the prescribed performance control strategy with a fixed-time sliding mode controller. This effectively limits the motor’s speed error within the predefined function boundaries, reduces system overshoo, and mitigates system jitter to a certain degree. Finally, simulation results are presented to validate that the proposed control strategy significantly enhances precision of speed tracking in PMLSMs.

Permanent-magnet linear motors (PMLMs) are widely used in various fields of industrial production, and the optimization design of the PMLM is increasingly attracting attention in order to improve the comprehensive performance of the motor. The primary problem of PMLM optimization design is the establishment of a motor model, and this paper summarizes the modeling of the PMLM electromagnetic field. First, PMLM parametric modeling methods (model-driven methods) such as the equivalent circuit method, analytical method, and finite element method, are introduced, and then non-parametric modeling methods (data-driven methods) such as the surrogate model and machine learning are introduced. Non-parametric modeling methods have the characteristics of higher accuracy and faster computation, and are the mainstream approach to motor modeling at present. However, surrogate models and traditional machine learning models such as support vector machine (SVM) and extreme learning machine (ELM) approaches have shortcomings in dealing with the high-dimensional data of motors, and some machine learning methods such as random forest (RF) require a large number of samples to obtain better modeling accuracy. Considering the modeling problem in the case of the high-dimensional electromagnetic field of the motor under the condition of a limited number of samples, this paper introduces the generative adversarial network (GAN) model and the application of the GAN in the electromagnetic field modeling of PMLM, and compares it with the mainstream machine learning models. Finally, the development of motor modeling that combines model-driven and data-driven methods is proposed.