Performance Of Permanent Magnet Synchronous Motor Research Articles

Combining finite-time control and prescribed tracking performance for uncertain PMSM driven steer-by-wire system with unknown disturbance

To solve the uncertainties in permanent magnet synchronous motor (PMSM) driven steer-by-wire (SbW) system, a prescribed-performance-control (PPC) based finite-time fuzzy controller is proposed. Specifically, the dynamics of SbW system driven by PMSM is analyzed, and combine PPC technology to transform the tracking error coordinates. Then, the velocity signal is obtained from the sigmoid function-based tracking differentiator by using the position signal. To solve the problem of mismatched disturbance, fuzzy logic system (FLS) are used as a universal approximator to estimate the lumped nonlinear friction and other unknown functions, the boundary of lumped disturbance is estimated by the designed adaptive updating law. By fusing the designed virtual controller and the intermediate control law, the controller needs no precise parameters of system, under which the effect of uncertainty of control gain can be compensated completely. Finally, rigorous theoretical analysis based on the Lyapunov stability theory is provided to demonstrate the finite-time stability of the closed-loop system under consideration. Simulation and experiment results are presented to show the effectiveness of the developed control approach, and some comparisons are given to show the rapid and accurate position tracking control performance.

Composite control based on FNTSMC and adaptive neural network for PMSM system

In this paper, a novel fixed-time non-singular terminal sliding mode control (NFNTSMC) method with an adaptive neural network (ANN) is proposed for permanent magnet synchronous motor (PMSM) system to improve PMSM performance. For nominal PMSM system without disturbance, a novel fixed-time non-singular terminal sliding mode control is designed to achieve fixed-time convergence property to improve the dynamic performance of the system. However, parameters mismatch and external load disturbances generally exist in PMSM system, the controller designed by NFNTSMC requires a large switching gain to ensure the robustness of the system, which will cause high-frequency sliding mode chattering. Therefore, an adaptive radial basis function (RBF) neural network is designed to approximate the unknown nonlinear lumped disturbance including parameters mismatch and external load disturbances online, and then the output of the neural network can be compensated to the NFNTSMC controller to reduce the switching gain and sliding mode chattering. Finally, the fixed-time convergence property and stability of the system are proved by Lyapunov method. The simulation and experimental results show that the presented strategy possesses satisfactory dynamic performance and strong robustness for PMSM system. And the proposed control scheme also provides an effective and systematic idea of the controller design for PMSM.

Comparison and analysis of power and torque performance of PMSM with different rotor structures

In this paper, according to the double reaction principle of permanent magnet synchronous motor (PMSM), the power, torque, and power angle characteristics are derived theoretically. Four motor models of tangential type, radial type, V-type, and U-type PMSM are established by finite element software. The magnetic flux density of the motor is analyzed in detail. At the same time, performance indicators such as efficiency, power factor, and air gap power of permanent magnet synchronous motors were calculated and evaluated, further improving the accuracy and credibility of the research. Based on the comparative study of the analysis results, the advantages and disadvantages of electromagnetic performance corresponding to different rotor structures are obtained, providing the design basis of PMSM.

Fuzzy compensation of model predictive control for PMSMs with external disturbances

In some high-speed scenarios, encoders may prove ineffective in providing real-time feedback, thereby increasing the installation and maintenance costs of Permanent Magnet Synchronous Motors (PMSMs). Consequently, the development of sensorless algorithms for medium and high-speed scenarios will enhance the practical applicability of PMSMs. In contrast to the angle estimation scheme for a rotated coordinate system, model predictive control (MPC) commences from the stationary coordinate system to explore Lyapunov stability and directly derive speed and angle based on the stability condition. The primary advantage of this approach lies in its ability to mitigate the accumulation of observation angle iteration errors, while simultaneously simplifying stability conditions. Furthermore, it is important to note that uncertain factors will significantly impede the performance of PMSMs. Subsequently, various fuzzy schemes are introduced to mitigate the impact of uncertain factors in the sensorless mode, and a rigorous proof is provided for the relationship between the fuzzy error and current error. Furthermore, a comprehensive analysis of controller stability conditions is conducted. Ultimately, experimental results demonstrate that the proposed fuzzy compensations effectively counteract external disturbances.

Exploring the Effects of Voltage Variation and Load on the Electrical and Thermal Performance of Permanent-Magnet Synchronous Motors

Europe has initiated the transition process toward IE4 efficiency motor classes, setting an example for other regions to follow in adopting higher-efficiency motor standards. However, in some regions, the operating voltage may differ from the nominal voltage according to the IEC 60038-2009. Therefore, the performance of new technologies under conditions of voltage variations (VVs) must also be assessed. This study presents a comprehensive analysis of a 0.75 kW line-start permanent-magnet motor (LSPMM) under different VV magnitudes, including undervoltage and overvoltage, while considering different load conditions. The study incorporates technical, economic, statistical, and thermal analyses to obtain important indicators related to power consumption, efficiency, power factor, and temperature. This study provides valuable insights to specialists regarding the technical and economic impacts of voltage-magnitude variation on LSPMMs.

Current decoupling control of permanent magnet synchronous motor based on improved nonlinear extended state observer

Precise current decoupling is required to achieve good control performance in the vector control of permanent magnet synchronous motor (PMSM), but traditional decoupling methods are unable to solve the problem of poor current decoupling effectiveness when the system inductance parameters are mismatched. Therefore, a decoupling control method of PMSM based on improved nonlinear extended state observer (INESO) is proposed in this paper. Firstly, a smooth, differentiable nonlinear function is used to replace the traditional fal function, which overcomes the problem of discontinuous gain changes. Secondly, a time-varying gain is designed to address the problem of reduced observer performance due to differential peak values in traditional NESO. Finally, the stability of INESO and the current loop closed-loop system is proven, followed by simulation and experimental verification. The simulation and experimental results show the proposed method effectively observes and compensates for system uncertainties, including parameter perturbations, external disturbances, and unmodeled dynamics. This method achieves complete decoupling of d and q-axes currents, while suppressing interference and enhancing the control performance of PMSM. The proposed INESO decoupling method reduces the d-axis current fluctuation about 96% and 90% when the load changes abruptly under motor inductance parameter mismatch, and can reduce q-axis current fluctuation about 88% and 78% when the d-axis current steps, respectively, compared with the conventional Current Feedback Decoupling Control (CFDC) and CDDC decoupling methods.

Design Optimization of an Automotive Permanent-Magnet Synchronous Motor by Combining DOE and NMGWO

This study proposes an optimization methodology for automotive permanent-magnet synchronous motors (PMSMs) to achieve maximum efficiency, maximum average torque, and minimum torque ripple. Many geometrical parameters can be used to define the PMSM of an automobile. To identify the most significant parameters for optimization, the fractional factorial design of the design of experiment (DOE) was employed for screening, considering the interaction effects. The central composite design was used to construct the proxy model between the optimization target and optimization variable, and the effectiveness of the model was judged. Aiming at the multi-objective optimization problem of a motor, a new mechanism for grey wolf optimizer (NMGWO) algorithm combining an elite reverse learning strategy, a local search strategy, and a nonlinear control parameter strategy is innovatively proposed. This algorithm was applied to solve the multi-objective optimization model. The numerical calculation results show that this is an effective optimization design method that can improve the performance of automotive PMSMs. The effectiveness of the NMGWO algorithm on the optimization results of permanent-magnet synchronous motors is verified by the experimental results.

Model-based robust servo control for permanent magnet synchronous motor with inequality constraint

Based on the dynamic model, a robust constrained control method for permanent magnet synchronous motor (PMSM) is proposed in this paper to achieve better trajectory tracking performance. Firstly, the constrained output variable of PMSM is transformed into unconstrained output variable by the monotone unbounded property of tangent function. After conversion, regardless of the uncertainty, the output angular displacement of PMSM always remains within the boundary. In addition, after state transformation of control variables, a new dynamic model of the system is obtained. Secondly, based on the new dynamic model, a control method based on model and error is proposed. Theoretical analysis shows that the proposed control satisfies the requirements of uniformly bounded and uniformly bounded limits. Thirdly, the practicability and effectiveness of the robust controller are verified by simulation and experiments. This method can restrain the influence of uncertainty well and improve the servo performance and operation reliability of PMSM significantly.

Stator current operation compensation (SCOC): A novel preprocessing method for deep learning-based fault diagnosis of permanent magnet synchronous motors under variable operating conditions

This paper proposes a novel preprocessing method, namely stator current operation compensation (SCOC), for deep learning-based fault diagnosis of a permanent magnet synchronous motor (PMSM) under variable operating conditions. To solve the problem that a change in operating conditions modifies characteristics of stator current signals in a way that makes it hard to discriminate fault modes, SCOC includes two stages: 1) tacho-less resampling and 2) main operating component subtraction with rescaling. First, the stator current signal is resampled to contain the same cycle for each deep learning input. Next, the signal is transformed to alleviate amplitude change by torque and to emphasize relatively small fault components. The effectiveness of the proposed method was validated by applying it to experimental data acquired under different types of PMSM operations. The results showed that each SCOC stage can reduce the variability between the data and effectively increase the fault diagnosis performance of PMSMs.

Comparative simulation study of electric motors for high performance of 3D printers

3D printing is a process in which material is joined layer by layer under computer control to make a 3D object easy to get almost any shape. This technology finds applications in various fields and it is attracting considerable interest from industry and academia. There are many different brands and models of motors used in 3D printers, and they all vary in quality and effectiveness. In this article we present the principal of the 3D printer, types of motors used in 3D printer and mathematical modelling of this motors like brushless direct current (DC) motor, permanent magnet synchronous motor (PMSM), and stepper motor. The models of analytical equations describing the three systems of motors are evaluated and developed by Matlab/Simunlink. In this paper, we have conducted a comparison of the series of results from simulation between the performance of PMSM, brushless DC and stepper motor. Among several criteria, this simulation study allows to select the criterion of response time to reach the desired speed and the precision of the rotor position to choose the most performant motor for 3D printers.

Analytical Method to Calculate Inductances of Spoke-Type Permanent-Magnet Synchronous Motors With Damping Bars

This paper proposes an analytical method to calculate inductances and resistances related to damping circuits of spoke-type permanent-magnet synchronous motor(PMSM) with damping bars. Harmonics of inductances are taken into account analytically in order to obtained performance of LSPMSM. Damping bars of spoke-type PMSM are divided into direct-axis and quadrature-axis damping circuits. The magnetic field, self-inductances and resistances of damping circuits and mutual inductances between damping circuits and stator winding are predicted analytically. The calculating results show that the inductances and resistances of spoke-type PMSM with damping bars by the proposed analytical method are well agreement with that predicted by finite-element method. The line-start process of spoke-type PMSM with multi-damping circuit model in which the inductances and resistances are calculated analytically is also similar with the experimental results. The finite-element and experimental results confirm that the developed analytical method has high accuracy for predicting inductances, resistances and performance of spoke-type PMSM.

Decoupled Speed and Flux Control of a Three-Phase Permanent Magnet Synchronous Motor under an Open-Circuit Fault Using a PR Current Controller

Presented in this article is a method for decoupling the speed and flux control of a three-phase permanent magnet synchronous motor (PMSM) during an open-circuit fault (OCF) using a current controller based on proportional resonant (PR) control techniques. The suggested control approach is relatively simple to implement and maintains good motor operation during the open circuit. PMSM performance under pre-fault, OCF, and post-fault conditions were investigated using Matlab/Simulink and an experimental setup based on a dSPACE DS1104. The conducted investigations provide strong evidence supporting the efficacy and resilience of the suggested control approach during OCF conditions.

Identification of Parameters and States in PMSMs

This paper discusses the importance of accurately identifying the parameters and states in permanent magnet synchronous motors (PMSMs) and their impact on motor performance and efficiency. This study was conducted to demonstrate the significance of these parameters. The results showed that inaccurate identification of the friction coefficient and moment of inertia led to poor motor performance, instability, and reduced efficiency. Accurate identification of these parameters is necessary for the proper control and operation of PMSMs. This paper highlights the various methods for calculating the friction coefficient and moment of inertia, as well as their potential limitations. The findings of this study emphasize the importance of accurately identifying these parameters for the efficient and effective operation of PMSMs.

A Generalized Per-Phase Equivalent Circuit Model of the PMSM With Predictable Core Loss

Equivalent circuit model (ECM) of the permanent magnet (PM) synchronous motor (PMSM) lays the foundation of the motor analysis, design, optimization, and control. However, the most widely used ECM of the PMSM ignores the core loss, which accounts for a considerable part of the electromagnetic loss and may exceed the copper loss in the medium and high-speed ranges. Previous researches of ECMs with predictable core loss are hard to satisfy the prediction precision over a broad range of speed and current. Therefore, a generalized per-phase ECM of the PMSM with predictable core loss is proposed. The proposed ECM topology and parameter identification method can effectively enhance the prediction accuracy of both the no-load and load core loss, and each component of the core loss in terms of the hysteresis, eddy current, and anomalous loss can be analyzed separately. Apart from the core loss, the proposed ECM has better precision in predicting the motor's output performance, such as mechanical characteristics, compared with traditional ECMs. The merits of the proposed ECM have been experimentally validated on the prototype of a PM transverse flux synchronous motor. This proposed ECM can be promotionally employed in other control strategies, such as model predictive control, to improve the PMSM performance.

Overview of Predictive Control Technology for Permanent Magnet Synchronous Motor Systems

Permanent magnet synchronous motors (PMSMs) are commonly used in the automation industry. With the speedy development of digital system processors, predictive control as a modern control scheme has been applied to improve the dynamic performance and work efficiency of PMSMs. This paper provides an overview of the research status of PMSM-based predictive control strategies. The deficiencies of the three most popular predictive schemes, deadbeat predictive control, finite-control-set model predictive control, and continuous-control-set model predictive control, and existing improvement strategies such as delay compensation schemes, robust control schemes, and multi-vector control schemes, are summarized. Finally, current technological trends are discussed, emphasizing future research directions for predictive control in PMSM drive systems.

A combined-pole permanent magnet synchronous motor incorporating nanocomposite magnets

The development of rare earth permanent magnet materials has made outstanding contributions to the advancement of high performance permanent magnet synchronous motors (PMSM). However, the non-renewable and strategic protection of rare earth resources leads to price fluctuations and supply risk of rare earth permanent magnets, limiting electrical vehicle development and popularity. In this paper, we optimized the design of the nanocomposite magnet microstructure and proposed a combined-pole interior nanocomposite permanent magnet synchronous motor (CP-INPMSM), combining nanocomposite magnet and PMSM. The simulation results show that the no-load back-electromotive force and torque of the motor are improved. This design can reduce the usage of rare-earth permanent magnet materials and improve the electromagnetic performance of the motor.

Modelling and analysis of electromagnetic force, vibration, and noise in permanent magnet synchronous motor for electric vehicles under different working conditions considering current harmonics

AbstractThe vibration and noise of the permanent magnet synchronous motor (PMSM) is mainly caused by its electromagnetic force. Harmonic currents affect the vibration, and noise performance of PMSM by influencing its electromagnetic force. The regularity of electromagnetic force, vibration, and noise characteristics of PMSM for electric vehicles (EVs) under different working conditions influenced by the harmonic currents is studied. Firstly, the analytical model of electromagnetic force under the action of a harmonic current is derived, and the influence of harmonic currents on the electromagnetic force of PMSM is summarised. Secondly, a multi‐physical field coupled vibration, and noise calculation model considering harmonic currents is established using the finite element method, and the vibration, and noise characteristics of PMSM under different operating conditions are analysed. The results show that the harmonic currents have different patterns of influence on the vibration, and noise of the PMSM due to the different advance angles and the saturation degree of the magnetic material under different working conditions. Finally, the validity of the theoretical analysis is verified by experiments, which has academic significance for vibration, and noise reduction of PMSMs for EVs.

Parameter Identification of Permanent Magnet Synchronous Motor Based on Improved MRAS Algorithm

During the operation of a permanent magnet synchronous motor, the electrical parameters of the motor will be affected by the temperature and the saturation of the magnetic chain, which will lead to a decrease in the effectiveness of the control algorithm for motor control. In this paper, we address the problem that the traditional MRAS algorithm has under-ranked equations when identifying motor parameters, and the three parameter identification values are coupled with each other and affect each other, which leads to scattered identification results and slow identification speed. In this paper, we propose a segmentation identification algorithm that combines the traditional MRAS algorithm with the recursive least squares method. In this paper, the inductance value is first identified by the recursive least squares method, and then the inductance value is substituted into the MRAS to identify the stator resistance and rotor magnetic chain, which effectively solves the problems of equation under-ranking and slow identification speed in the traditional MRAS, thus improving the stability of the permanent magnet synchronous motor operation.

Performance Improvement of DTC-SVM of PMSM with Compensation for the Dead Time Effect and Power Switch Loss Based on Extended Kalman Filter

Two algorithms have been extensively studied for motor control: Field Oriented Control (FOC) and Direct Torque Control (DTC). Both control algorithms use a Voltage Source Inverter (VSI) to drive a Permanent Magnet Synchronous Motor (PMSM). To prevent short-arm short-circuit accidents when driving PMSM using VSI, a dead time is used to turn off the TOP and BOTTOM switches of each arm at the same time. However, this dead-time technique causes an unexpected pole voltage to be applied to the PMSM on the VSI output voltage, causing distortion and resulting in control nonlinearity. The disturbance voltage that causes nonlinearity is difficult to measure directly with the sensor. Therefore, this paper analyzes the nonlinearity of the controller due to the distorted voltage caused by the dead time during PMSM operation using the DTC algorithm and predicts the distorted output voltage using the extended Kalman Filter (EKF) to improve control stability. As a result, The algorithm proposed in this paper has verified the improvement of torque ripple and stator flux ripple through experiments and simulations.

Harmonic error observation of permanent magnet synchronous motor and its angle lag compensation method

During the permanent magnet synchronous motor operation, the inherent back-EMF output voltage harmonics of the permanent magnet synchronous motor shows the high harmonic noise signal, which is not conducive to the high precision control system. The harmonic error compensation method based on feedforward compensation is adopted to solve this problem and improve the system response characteristics and control accuracy. Firstly, in this paper, the torque harmonic error of a 12-pole 18-slot permanent magnet synchronous motor is analyzed and compensated. Then, this paper compensates the lag problem, which caused by the lag phase of the space voltage vector and harmonic lag. Finally, the experimental and observational simulation analysis results show that the method proposed in this paper can effectively suppress the error caused by the signal sampling lag. And the observation accuracy of permanent magnet synchronous motor is significantly improved.